CN114904280A - Resource allocation method, device, equipment and medium - Google Patents
Resource allocation method, device, equipment and medium Download PDFInfo
- Publication number
- CN114904280A CN114904280A CN202210455871.7A CN202210455871A CN114904280A CN 114904280 A CN114904280 A CN 114904280A CN 202210455871 A CN202210455871 A CN 202210455871A CN 114904280 A CN114904280 A CN 114904280A
- Authority
- CN
- China
- Prior art keywords
- visit
- pet
- information
- cluster
- resource configuration
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000013468 resource allocation Methods 0.000 title claims abstract description 55
- 238000000034 method Methods 0.000 title claims abstract description 51
- 238000003745 diagnosis Methods 0.000 claims abstract description 24
- 238000004590 computer program Methods 0.000 claims description 21
- 238000012552 review Methods 0.000 claims description 14
- 238000003860 storage Methods 0.000 claims description 13
- 238000012545 processing Methods 0.000 claims description 11
- 238000004891 communication Methods 0.000 description 11
- 238000010586 diagram Methods 0.000 description 6
- 230000009286 beneficial effect Effects 0.000 description 4
- 201000010099 disease Diseases 0.000 description 4
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 235000013305 food Nutrition 0.000 description 4
- 230000003796 beauty Effects 0.000 description 3
- 239000003814 drug Substances 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 230000008520 organization Effects 0.000 description 2
- 241000271566 Aves Species 0.000 description 1
- 241000282472 Canis lupus familiaris Species 0.000 description 1
- 206010012735 Diarrhoea Diseases 0.000 description 1
- 241000282326 Felis catus Species 0.000 description 1
- 241000287828 Gallus gallus Species 0.000 description 1
- 241000270290 Gekkota Species 0.000 description 1
- 241000270322 Lepidosauria Species 0.000 description 1
- 241000282320 Panthera leo Species 0.000 description 1
- 241000270295 Serpentes Species 0.000 description 1
- 241000270666 Testudines Species 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 235000013330 chicken meat Nutrition 0.000 description 1
- 238000012790 confirmation Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 229940079593 drug Drugs 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 230000003340 mental effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000004962 physiological condition Effects 0.000 description 1
- 230000035935 pregnancy Effects 0.000 description 1
- 229960005486 vaccine Drugs 0.000 description 1
Images
Classifications
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
- A63F13/80—Special adaptations for executing a specific game genre or game mode
- A63F13/825—Fostering virtual characters
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
- A63F13/30—Interconnection arrangements between game servers and game devices; Interconnection arrangements between game devices; Interconnection arrangements between game servers
- A63F13/33—Interconnection arrangements between game servers and game devices; Interconnection arrangements between game devices; Interconnection arrangements between game servers using wide area network [WAN] connections
- A63F13/335—Interconnection arrangements between game servers and game devices; Interconnection arrangements between game devices; Interconnection arrangements between game servers using wide area network [WAN] connections using Internet
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
- G06F16/2228—Indexing structures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2457—Query processing with adaptation to user needs
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06313—Resource planning in a project environment
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F2300/00—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game
- A63F2300/50—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game characterized by details of game servers
- A63F2300/57—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game characterized by details of game servers details of game services offered to the player
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Theoretical Computer Science (AREA)
- Multimedia (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Databases & Information Systems (AREA)
- Entrepreneurship & Innovation (AREA)
- General Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Biodiversity & Conservation Biology (AREA)
- Operations Research (AREA)
- Educational Administration (AREA)
- Life Sciences & Earth Sciences (AREA)
- Game Theory and Decision Science (AREA)
- Software Systems (AREA)
- Marketing (AREA)
- Development Economics (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Computational Linguistics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Measuring And Recording Apparatus For Diagnosis (AREA)
Abstract
The embodiment of the application provides a resource configuration method, a device, equipment and a medium, wherein the method comprises the following steps: acquiring a pet information set of a virtual pet cluster in a target area and a first resource configuration corresponding to the virtual pet cluster in a virtual pet hospital in the target area; acquiring a diagnosis information set of an entity pet cluster similar to the virtual pet cluster based on the pet information set of the virtual pet cluster; acquiring the visit demand information of the virtual pet cluster based on the visit information set of the entity pet cluster; acquiring a matching value between the diagnosis requirement information and the diagnosis capability information corresponding to the first resource allocation; and if the matching value is smaller than the preset threshold value, adjusting the first resource allocation to increase the resources corresponding to the virtual pet cluster. By adopting the embodiment of the application, the rationality of resource allocation in the virtual pet hospital can be improved.
Description
Technical Field
The present application relates to the field of internet technologies, and in particular, to a method, an apparatus, a device, and a medium for resource allocation.
Background
With the satisfaction of the material demand, raising pets becomes a way to meet the mental demand. And with the development of internet technology, more and more users choose to feed virtual pets on the internet instead of physical pets. Currently, in order to improve the reality of virtual pets, virtual pets are ill like physical pets. And the virtual pet can be recovered after the doctor visits or feeds the corresponding medicine in the hospital. If the number of hospitals in the world corresponding to the virtual pet is insufficient, or the number of medical staff in related departments is insufficient or the level is insufficient, the queuing time is increased, and even the condition of the virtual pet is aggravated. Therefore, how to configure the resources of the virtual pet hospital is a technical problem to be solved by those skilled in the art.
Disclosure of Invention
The embodiment of the application provides a resource allocation method, a resource allocation device and a resource allocation medium, which can improve the rationality of resource allocation in a virtual pet hospital.
An aspect of the present embodiment provides a resource allocation method, including:
acquiring a pet information set of a virtual pet cluster in a target area and a first resource configuration corresponding to the virtual pet cluster in a virtual pet hospital in the target area;
acquiring a visit information set of an entity pet cluster similar to the virtual pet cluster based on the pet information set;
acquiring the visit demand information of the virtual pet cluster based on the visit information set;
acquiring a matching value between the visit demand information and the visit capacity information corresponding to the first resource configuration;
and if the matching value is smaller than the preset threshold value, adjusting the first resource allocation to increase the resources corresponding to the virtual pet cluster.
An aspect of the present application provides a resource allocation apparatus, including:
the system comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring a pet information set of a virtual pet cluster in a target area and a first resource configuration corresponding to the virtual pet cluster in a virtual pet hospital in the target area;
the second acquisition unit is used for acquiring the visit information set of the entity pet cluster similar to the virtual pet cluster based on the pet information set;
the third acquisition unit is used for acquiring the visit demand information of the virtual pet cluster based on the visit information set;
the fourth acquiring unit is used for acquiring a matching value between the visit demand information and the visit capability information corresponding to the first resource configuration;
and the adjusting unit is used for adjusting the first resource allocation to increase the resources corresponding to the virtual pet cluster if the matching value is smaller than the preset threshold.
An aspect of an embodiment of the present application provides a computer device including a memory and a processor connected to the memory. Wherein the memory is configured to store a computer program, and the processor is configured to invoke the computer program to cause the computer device to perform the method provided by the above-mentioned aspect in the embodiments of the present application.
An aspect of an embodiment of the present application provides a computer-readable storage medium. The computer-readable storage medium has stored therein a computer program adapted to be loaded and executed by a processor, so as to cause a computer device having the processor to execute the method provided by the above-mentioned aspect in the embodiments of the present application.
According to an aspect of the application, a computer program product or computer program is provided. The computer program product or computer program comprises computer instructions, which are stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions to cause the computer device to perform the method provided by the above-mentioned aspect.
The embodiment of the application can acquire the diagnosis information set of the entity pet cluster similar to the virtual pet cluster based on the pet information set of the virtual pet cluster in the target area. And acquiring the diagnosis requirement information of the virtual pet cluster based on the diagnosis information set of the entity pet cluster. Therefore, the diagnosis requirement of the virtual pet is predicted according to the actually-occurring diagnosis event, and the accuracy of obtaining the diagnosis requirement information can be improved. And then acquiring a matching value between the visit demand information of the virtual pet cluster and the visit capability information corresponding to the virtual pet cluster in the virtual pet hospital. And under the condition that the matching value is smaller than the threshold value, adjusting the resource configuration corresponding to the virtual pet cluster in the virtual pet hospital to increase the resources corresponding to the virtual pet cluster. Therefore, the reasonability of resource allocation in the virtual pet hospital can be improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a network architecture according to an embodiment of the present application;
FIG. 2 is a schematic view of a virtual pet clinic scenario provided in an embodiment of the present application;
fig. 3 is a flowchart illustrating a resource allocation method according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a resource allocation apparatus according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a computer device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In the embodiment of the present application, the pet in the real world is referred to as a physical pet, for example, a first physical pet, a second physical pet, and the like. Pets in a networked environment are referred to as virtual pets, or cyber pets, or the like. It should be noted that the pet food may be real pet food in the real world, or may be virtual pet food generated in a network environment for increasing reality.
The object corresponding to the pet can be the owner or custodian of the pet, and the like. The number of objects corresponding to the pet may be 1, 2 or more, and is not limited herein.
The pet type is not limited in the present application, and may include common cats, dogs, birds, turtles, etc., and may also include unusual chickens, hog snakes, lizards, geckos, lions, etc.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a network architecture according to an embodiment of the present disclosure. As shown in fig. 1, the network architecture may include a server 10d and a user terminal cluster, which may include one or more user terminals, where the number of user terminals is not limited. As shown in fig. 1, the user terminal cluster may specifically include a user terminal 10a, a user terminal 10b, a user terminal 10c, and the like.
The server 10d may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a network service, cloud communication, a middleware service, a domain name service, a security service, a Content Delivery Network (CDN), a big data and artificial intelligence platform, and the like.
The user terminal 10a, the user terminal 10b, the user terminal 10c, and the like may each include: the electronic device comprises an electronic device with a video/image playing function, such as a smart phone, a tablet computer, a notebook computer, a palm computer, a Mobile Internet Device (MID), a wearable device (such as a smart watch, a smart bracelet and the like), an intelligent voice interaction device, an intelligent household appliance (such as a smart television and the like), a vehicle-mounted device and the like.
As shown in fig. 1, the user terminal 10a, the user terminal 10b, the user terminal 10c, etc. may be respectively connected to the server 10d via a network, so that each user terminal may interact data with the server 10d via the network. For example, the user terminal 10a may transmit pet information of the virtual pet to the server 10 d. The user terminal 10a may also transmit object information corresponding to the virtual pet to the server 10 d. The server 10d may transmit a suggestion message of resource configuration or the like to the user terminal 10 a.
In an embodiment of the present application, the pet information may include identification information of the pet (e.g., name, nasal print image, identification of the subject, etc.), pet attributes such as breed, age, sex, weight, height, etc. The pet information may also include event data of the pet, such as a cause of a visit, a visit record, a diagnosis manner, etc. in the event of a visit, a race type, a ranking, etc. in the event of a race, a beauty event, etc. in the event of a beauty. The content of the pet information is not limited in the present application.
The object information may include object properties of the object, instant event data, historical event data, and the like. The object attributes may include identification information (e.g., name, identity, account identification, etc.) of the object, basic information such as age, gender, occupation, address, etc., and may also include social data of the object, such as social relationships in a network or real life. Object properties may alternatively include tags of the object, e.g., hobbies, behavior habits, etc.
The instant event data may include data related to the current use of the user terminal 10a by the object, such as keywords currently searched, contents browsed, and the like. The historical event data may include shopping records, browsing records, etc. of prior uses of the user terminal 10a or other user terminals by the object. The instant event data and the historical event data may alternatively include information about the pet by the subject, such as review information for pet food, review information for pet hospitals, review information for pet beauty salons, review information for pet amusement parks, and the like. The comment information is used for describing the preference of the object, and is explained by taking a pet hospital as an example, and the comment information can be used for the price, service, health condition, diagnosis effect and the like of the hospital. The present application is not limited to the object information.
The pet information and the object information may be uploaded to a server and stored, or may be stored in a Blockchain (Blockchain). The block chain in the embodiment of the application is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. The blockchain is essentially a decentralized database, which is a string of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, which is used for verifying the validity (anti-counterfeiting) of the information and generating the next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like. Therefore, data are stored in a distributed mode through the block chains, data security is guaranteed, and meanwhile data sharing of information among different platforms can be achieved.
The following description will take the user terminal 10a as an example, and a scene of a virtual pet visit as an example. Referring to fig. 2, fig. 2 is a schematic view of a virtual pet clinic scenario provided in the embodiment of the present application. As shown in fig. 2, an object 101 (e.g., a host or a custodian) corresponding to a virtual pet 201 may receive a disease reminder transmitted from a server 10d through a user terminal 10 a. The subject 101 may then click on the area of the virtual pet hospital 202 so that the virtual pet 201 may enter the scene of the virtual pet hospital 202 and accept the diagnosis of the virtual medical personnel 203 in the virtual pet hospital 202.
In a portion not shown in fig. 2, the subject 101 may acquire the diagnosis result of the virtual pet 201 through the contents displayed in the user terminal 10 a. The subject 101 may perform links such as payment and medication taking through the user terminal 10a, and may also perform comments on the present visit, which is not limited herein.
Currently, in order to improve the reality of a virtual pet, the virtual pet may be ill like a physical pet. And the virtual pet can be recovered after the doctor visits or feeds the corresponding medicine in the hospital. If the number of hospitals in the world corresponding to the virtual pet is insufficient, or the number or level of medical staff in the relevant department is insufficient, the queuing time is increased, and even the condition of the virtual pet is aggravated.
Based on this, the application provides a resource allocation method. The method may be performed by a computer device, which may be a server (e.g., the server 10d in the embodiment corresponding to fig. 1), or a user terminal (e.g., any one of the user terminals in the user terminal cluster shown in fig. 1), or a computer program (including program code), etc.
Specifically, referring to fig. 3, fig. 3 is a schematic flowchart of a resource allocation method according to an embodiment of the present disclosure. As shown in fig. 3, the method includes the following steps S301 to S305, wherein:
step S301: the method comprises the steps of obtaining a pet information set of a virtual pet cluster in a target area and first resource allocation corresponding to the virtual pet cluster in a virtual pet hospital in the target area.
The target area is not limited in the present application, and may be any area in the world corresponding to the virtual pet, or an area divided by a city, a county, or a district level. It should be noted that, when the world corresponding to the virtual pet is updated along with the map in the real world, the target area may be a virtual area corresponding to an area actually existing in the real world.
The virtual pet cluster comprises a plurality of virtual pets, and the pet information set comprises pet information corresponding to each virtual pet. The pet information can refer to the foregoing or the following, and is not repeated herein, and the number and the type of the virtual pets are not limited in the present application. It should be noted that the virtual pets in the virtual pet cluster may be virtual pets of the same breed. Or further, the virtual pets may be of the same type, for example, the virtual pets with the same breed, gender and age and the weight difference satisfying the threshold interval are classified into a virtual pet cluster.
The virtual pet hospital can configure different virtual medical personnel and virtual medical equipment aiming at various virtual pet clusters. It should be noted that virtual medical personnel and virtual medical devices may correspond to 1 or more than 1 virtual pet cluster. That is, virtual medical personnel or virtual medical devices may be used for different virtual pet clusters. The first resource allocation may include the number and seniority of virtual medical care providers configured for the virtual pet cluster in the current virtual pet hospital, the number and attributes of virtual medical devices, and the like, which is not limited herein.
Alternatively, in the first case, step S301 is performed. The first condition may be that a preset fixed time period (for example, one month or the like) arrives, or the evaluation value received by the virtual pet hospital or the virtual pet cluster in the virtual pet hospital is less than a threshold (for example, 0.7 or the like), or may be a time period in which the virtual pet cluster is vulnerable or an entity pet is suffering from an epidemic disease or the like, which is not limited herein.
Step S302: and acquiring a visit information set of the entity pet cluster similar to the virtual pet cluster based on the pet information set of the virtual pet cluster.
In the embodiment of the application, the entity pet cluster corresponds to the virtual pet cluster, and may include entity pets of the same kind as the virtual pet in real life. The visit information set can comprise the content corresponding to the information generated when the entity pet in the entity pet cluster visits the doctor. Or the pet information of the entity pet, the object information corresponding to the entity pet, and the like can be included. The method for clustering the physical pets, acquiring the visit information set and acquiring the physical pet cluster and the visit information set is not limited in the application. It is understood that the visit information set of the entity pet cluster similar to the virtual pet cluster is obtained based on the pet information set. That is, the information such as the morbidity, the cure rate and the treatment duration of the virtual pet is predicted based on the treatment information of the physical pet, which is beneficial to improving the rationality of resource allocation.
In one possible example, step S302 may include the following step a1 to step A3, wherein:
step A1: determining a similar physical pet cluster of the virtual pet cluster based on the pet information set of the virtual pet cluster.
In the embodiment of the application, the entity pet cluster can be searched by judging whether the pet information set of the entity pet cluster is similar to the pet information set of the virtual pet cluster. Optionally, a tag set of the virtual pet cluster is obtained based on the pet information set of the virtual pet cluster; and searching the entity pet corresponding to the label set of the virtual pet cluster to serve as the entity pet cluster similar to the virtual pet cluster.
Wherein the labelset comprises characteristics of a virtual pet cluster. As such, pets similar to the virtual pet cluster, e.g., a physical pet cluster similar to the virtual pet cluster, may be able to be found based on the set of tags. The number of the labels in the label set can be 1, 2 or more, and each label can be described in the form of a key-value pair (key-value), that is, the attribute type is used as a key element, and the attribute information is used as a value element. Or the attribute information may be adopted alone as the tag. The tag set may include characteristics of the virtual pet cluster, such as breed, age, gender, weight, and hobbies, and is not limited herein.
Step A2: and searching a diagnosis record set of the entity pets in the entity pet cluster.
Step A3: and processing the visit record set to obtain a visit information set of the entity pet cluster.
In an embodiment of the present application, the visit record set may include visit records of physical pets in the physical pet cluster. The visit information set can be understood as the content processed by the visit record set. The method for processing the visit record set is not limited in the present application, and the method may be classified based on the type of the visit, or may be classified based on the duration of the visit, or may be classified based on the cure rate, etc.
As illustrated below by classifying the visit types, in a possible example, the visit information set includes the visit probability and the visit duration corresponding to the visit type, and step a3 may include the following steps: dividing the visit record set to obtain a visit record subset corresponding to the visit type; acquiring the treatment duration corresponding to the treatment type based on the time information in the treatment record subset; and obtaining the ratio of the number of the pets to be treated corresponding to the treatment type to the number of the pets in the entity pet cluster, and obtaining the treatment probability corresponding to the treatment type.
The medical treatment type may include a disease type such as a cold, diarrhea, burn, etc., or may include an event type such as a vaccine, physical examination, etc., or may include a physiological type such as production, ligation, pregnancy, etc., which is not limited herein.
The visit probability refers to the probability of visiting a hospital when the matters corresponding to the visit type occur. It will be appreciated that different types of pets may develop different types of disease and that there may be differences in the corresponding cure rates for the same type of pet at different ages or under different physiological conditions. Therefore, in this example, the set of visit records is divided by the type of the visit, resulting in a subset of the visit records corresponding to different visit queues. And then the treatment probability corresponding to the treatment type is obtained according to the ratio of the number of the treated pets to the number of the pets in the whole entity pet cluster, and the treatment duration corresponding to the treatment type is obtained according to the time information in the treatment record subset, so that the accuracy of obtaining the treatment information can be improved, and the rationality of resource allocation is favorably improved.
It is to be understood that, in the steps A1-A3, the physical pet cluster similar to the virtual pet cluster is determined based on the pet information set of the virtual pet cluster. And then processing the visit record set of the entity pets in the entity pet cluster to obtain the visit information set of the entity pet cluster. Therefore, the accuracy of obtaining the information of seeing a doctor can be improved, and the reasonability of resource allocation is favorably improved.
Step S303: and acquiring the visit demand information of the virtual pet cluster based on the visit information set of the entity pet cluster.
In this embodiment of the application, the visit demand information may include the number and level of medical care personnel required for the virtual pet cluster to visit, and may further include the number of medical devices, the diagnosis duration, and the like. The visit need information may alternatively include the length of the visit need. The visit required duration refers to the time information required by the virtual pet to visit. The visit required duration may include a diagnosis duration required by the virtual medical staff and/or the virtual medical equipment when the virtual pet is diagnosed. The visit duration may be an average time, a maximum time, a minimum time, or a time range, and is not limited herein.
It can be understood that the larger the number of virtual pets in the virtual pet cluster, the more medical staff and medical equipment are required, and the longer the visit time is. The visit information set carries the visit information of the entity pet cluster similar to the virtual pet cluster, so that the information required by the current virtual pet cluster during the visit, namely the visit demand information, can be judged based on the visit information and the number of virtual pets in the virtual pet cluster.
In a possible example, the visit demand information includes a visit demand duration corresponding to the visit type, and step S303 may include: and acquiring the product of the treatment probability corresponding to the treatment type and the treatment duration to obtain the treatment demand duration corresponding to the treatment type.
The length of the visit requirement can be referred to the above or the following, and is not described herein again. It can be understood that the product between the visit probability corresponding to the visit type and the visit duration is equivalent to the product between the attack probability of the virtual pet needing to be visited in the virtual pet cluster and the visit duration. The product is used as the length of the time required for the treatment corresponding to the treatment type, so that the accuracy of obtaining the length of the time required for the treatment can be improved, and the rationality of resource allocation can be improved.
Step S304: and acquiring a matching value between the visit demand information and the visit capability information corresponding to the first resource configuration.
In the embodiment of the present application, the matching value is used to describe the similarity between the visit requirement information and the first resource configuration. The matching value may be equal to a similarity value between the visit demand information and the visit capability information corresponding to the first resource configuration, or may specifically be equal to a ratio between the visit demand duration and the visit capability duration corresponding to the first resource configuration, and the like, which is not limited herein.
As illustrated below by using a sub-resource configuration corresponding to one visit type in the first resource configuration, and the matching value being a sub-matching value corresponding to the visit type, in a possible example, the step S304 may include the following steps: acquiring the length of the visit capability corresponding to the sub-resource configuration; and acquiring the ratio of the time required for seeing a doctor to the time of seeing a doctor capability to obtain a sub-matching value corresponding to the type of seeing a doctor.
The length of the visit capability refers to the time information required by the virtual pet hospital for the type of the visit. The length of visit capability may include a length of diagnosis capability of the virtual medical personnel and/or the virtual medical device, etc. The length of the visit ability can be an average time, a maximum time, a minimum time, or the like, or a time range, and the like, and is not limited herein.
It can be understood that, in this example, the ratio between the visit demand duration corresponding to one visit type and the visit capability duration corresponding to the sub-resource configuration corresponding to the visit type is used as the sub-matching value corresponding to the visit type. The matching value between the visit demand information and the first resource allocation can be equal to the set of the sub-matching values corresponding to the visit types, or can be equal to the weighted value of the sub-matching values corresponding to the visit types, so that the accuracy rate of determining whether the resources of the current virtual pet hospital are reasonable can be improved, and the rationality of the resource allocation is favorably improved.
Step S305: and if the matching value is smaller than the preset threshold value, adjusting the first resource allocation to increase the resources corresponding to the virtual pet cluster.
The preset threshold is not limited in the present application, and may be a preset fixed value, for example, 60%. Or may be determined based on the number of virtual pets in the virtual pet cluster, the subject consumption level corresponding to the virtual pet, the probability of encounter, etc. It can be understood that, in the case that the matching value is smaller than the preset threshold, the first resource configuration is less, and the resource needs to be increased. In the case that the matching value is greater than or equal to the preset threshold, the first resource configuration may not be adjusted. Thus, the rationality of resource allocation can be improved.
For example, assuming that the first resource configuration corresponding to the virtual pet cluster in the virtual pet hospital in the target area is { doctor 1, nurse 2, and medical device 1 }, the matching value between the visit demand information and the visit capability information corresponding to the first resource configuration is 0.5, and the preset threshold value is 0.6, the first resource configuration needs to be adjusted, for example, the first resource configuration is adjusted to { doctor 2, nurse 2, and medical device 2 }.
The method for adjusting the first resource configuration is not limited in the present application, and may be adjusted based on the size of the matching value, or in a possible example, the method for adjusting the first resource configuration may include the following steps B1 and B2, where:
step B1: and acquiring second resource configuration and comment information corresponding to the entity pet cluster in the entity pet hospital.
The second resource allocation may refer to the description of the first resource allocation, and is not described herein again. The physical pet hospital may be a visit pet hospital corresponding to the visit information set, or may be a pet hospital in which the same type of subject as the subject corresponding to the virtual pet may take the physical pet to visit, or may be a pet hospital in a physical area corresponding to the target area, and the like, which is not limited herein.
In one possible example, before step B1, the following steps may be further included: acquiring an object information set corresponding to the virtual pet cluster; and searching the entity pet hospital based on the pet information set and the object information set.
The object information set includes object information corresponding to virtual pets in the virtual pet cluster, or content corresponding to the object information, for example, tag information of the object. The contents of the object information can be referred to the above or below, and are not limited herein.
It can be understood that the entity pet hospital is searched from the pet information set of the virtual pet cluster and the object information set corresponding to the virtual pet cluster, so that the reference item of the entity pet hospital to the virtual pet hospital can be improved, and the rationality of resource allocation is favorably improved.
In the embodiment of the application, the comment information may be an opinion or suggestion that an object (e.g., an owner or a custodian, etc.) corresponding to the entity pet cluster makes for an entity pet hospital, a medical care worker or a medical device corresponding to a visit type, and the like. The comment information may be searched from a server corresponding to the entity pet hospital, or may be searched from a server or a platform (for example, a platform on which an object corresponding to the entity pet cluster frequently issues a status) other than the server corresponding to the entity pet hospital based on keywords related to the entity pet hospital, medical staff or medical equipment corresponding to the type of doctor, or the like, which is not limited herein.
Step B2: and adjusting the first resource configuration based on the second resource configuration and the comment information.
The adjusting method of the first resource configuration may include adjusting based on a difference configuration between the first resource configuration and the second resource configuration and an object focus point corresponding to the comment information, which is not limited herein. In one possible example, step B2 may include the steps of: obtaining a rating value of the second resource configuration based on the comment information; obtaining a similarity value between the first resource configuration and the second resource configuration; determining an optimized resource dimension and a target value of the first resource configuration based on the score value and the similarity value; the first resource configuration is adjusted based on the optimized resource dimension and the target value.
And the score value is used for describing the satisfaction degree of the object corresponding to the entity pet in the entity pet cluster to the second resource allocation. The scoring value may be obtained based on a reasonable value of the second resource allocation, and/or the review information of the object may be obtained for the review information of the second resource allocation, and the like, which is not limited herein. The reasonable value of the second resource allocation can be evaluated from the aspects of the medical staff's academic history, working experience, quantity and the like, and the aspects of the updating degree, accuracy and the like of the medical equipment. The comment information of the comment information for the second resource configuration may be determined from the content in the comment information, for example, good, satisfactory, unsatisfactory, bad, and so on adjectives, or evaluated based on the semantics of the comment information, and so on, without limitation.
The similarity value is used to describe a degree of similarity between the first resource configuration and the second resource configuration. The review information may be obtained by comparing the sub-resource configurations corresponding to the respective visit types, or may be obtained by comparing the review information corresponding to the first resource configuration with the review information corresponding to the second resource configuration, and the like, which is not limited herein.
The optimized resource dimension refers to a resource dimension to be optimized in the first resource configuration, for example, service attitude, communication efficiency, professionality, and the like. The target value may be a value that can be reached after the resource optimization corresponding to the optimized resource dimension is performed, or a value to be increased, and the like.
It is understood that, in this example, the optimized resource dimension to be optimized and the optimized target value in the first resource configuration are determined from the value of the comment of the object corresponding to the entity pet cluster on the second resource configuration and the value of similarity between the first resource configuration and the second resource configuration. And then, the first resource configuration is adjusted based on the optimized resource dimension and the target value, so that the accuracy of adjusting the first resource configuration can be improved, and the rationality of the resource configuration can be further improved.
In the method shown in fig. 3, a visit information set of a physical pet cluster similar to a virtual pet cluster in a target area is obtained based on a pet information set of the virtual pet cluster. And acquiring the visit demand information of the virtual pet cluster based on the visit information set of the entity pet cluster. Therefore, the diagnosis requirement of the virtual pet is predicted according to the actually-occurring diagnosis event, and the accuracy of obtaining the diagnosis requirement information can be improved. And then acquiring a matching value between the visit demand information of the virtual pet cluster and the visit capability information corresponding to the virtual pet cluster in the virtual pet hospital. And under the condition that the matching value is smaller than the threshold value, adjusting the resource configuration corresponding to the virtual pet cluster in the virtual pet hospital to increase the resources corresponding to the virtual pet cluster. Therefore, the reasonability of resource allocation in the virtual pet hospital can be improved.
In another possible example, if the matching value is smaller than the first threshold and larger than the second threshold, the first resource allocation is adjusted to increase the resources corresponding to the virtual pet cluster; or if the matching value is less than or equal to the second threshold value, increasing the number of virtual pet hospitals in the target area.
Wherein the first threshold is greater than the second threshold. The first threshold may be the preset threshold, and the first threshold and the second threshold are not limited in this application, and reference may be made to the description of the preset threshold. It can be understood that, if the matching value is smaller than the first threshold and larger than the second threshold, the first resource allocation may be adjusted to increase the resources corresponding to the virtual pet cluster. If the match value is less than or equal to the second threshold, the number of virtual pet hospitals within the target area may be increased to increase resources within the target area. Therefore, resources of the virtual pet hospital are increased in a planned manner, and the reasonability of resource allocation is improved.
It should be noted that, when acquiring data such as object information of a user, pet information raised by the user, resource configuration of a hospital, and the like, the computer device in the embodiment of the present application may display a prompt interface or a pop-up window, where the prompt interface or the pop-up window is used to prompt the user to currently collect the object information of the user, the pet information raised by the user, the resource configuration of the hospital, and the like, and only after acquiring that the user sends a confirmation operation to the prompt interface or the pop-up window, the computer device starts to execute a relevant step of data acquisition, otherwise, the computer device ends.
It is understood that in the specific embodiments of the present application, business data of the user, enterprise, organization and other objects (for example, object information of the user, pet information of the user, resource allocation of the hospital and other data) may be involved, when the above embodiments of the present application are applied to specific products or technologies, permission or consent of the user, enterprise, organization and other objects needs to be obtained, and the collection, use and processing of the relevant data need to comply with relevant laws and regulations and standards of relevant countries and regions.
The method of the embodiments of the present application is set forth above in detail and the apparatus of the embodiments of the present application is provided below.
Referring to fig. 4, fig. 4 is a schematic structural diagram of a resource allocation apparatus according to an embodiment of the present disclosure. As shown in fig. 4, the resource allocation apparatus 400 includes a first obtaining unit 401, a second obtaining unit 402, a third obtaining unit 403, a fourth obtaining unit 404, a fifth obtaining unit 405, and an adjusting unit 406, where:
the first obtaining unit 401 is configured to obtain a pet information set of a virtual pet cluster in a target area and a first resource configuration corresponding to the virtual pet cluster in a virtual pet hospital in the target area;
the second obtaining unit 402 is configured to obtain a visit information set of an entity pet cluster similar to the virtual pet cluster based on the pet information set;
the third obtaining unit 403 is configured to obtain the visit demand information of the virtual pet cluster based on the visit information set;
the fourth obtaining unit 404 is configured to obtain a matching value between the visit demand information and the visit capability information corresponding to the first resource configuration;
the adjusting unit 406 is configured to adjust the first resource allocation to increase the resource corresponding to the virtual pet cluster if the matching value is smaller than the preset threshold.
In a possible example, the second obtaining unit 402 is specifically configured to obtain a tag set of the virtual pet cluster based on the pet information set; determining a similar entity pet cluster of the virtual pet cluster based on the label set; searching a diagnosis record set of the entity pets in the entity pet cluster; and processing the visit record set to obtain a visit information set of the entity pet cluster.
In a possible example, the visit information set includes a visit probability and a visit duration corresponding to the visit type, and the second obtaining unit 402 is specifically configured to divide the visit record set to obtain a visit record subset corresponding to the visit type; acquiring the treatment duration corresponding to the treatment type based on the time information in the treatment record subset; and obtaining the ratio of the number of the pets to be treated corresponding to the treatment type to the number of the pets in the entity pet cluster, and obtaining the treatment probability corresponding to the treatment type.
In a possible example, the visit demand information includes a visit demand duration corresponding to the visit type, and the third obtaining unit 403 is specifically configured to obtain a product between the visit probability corresponding to the visit type and the visit duration to obtain the visit demand duration corresponding to the visit type.
In one possible example, the first resource configuration includes a sub-resource configuration corresponding to the visit type, and the matching value includes a sub-matching value corresponding to the visit type; the fourth obtaining unit 404 is specifically configured to obtain the length of the visit capability corresponding to the sub-resource configuration; and acquiring the ratio of the time required for seeing a doctor to the time of seeing a doctor capability to obtain a sub-matching value corresponding to the type of seeing a doctor.
In a possible example, the adjusting unit 406 is specifically configured to obtain a second resource configuration and comment information corresponding to a physical pet cluster in a physical pet hospital; and adjusting the first resource configuration based on the second resource configuration and the comment information.
In a possible example, the fifth obtaining unit 405 is configured to obtain a set of object information corresponding to a virtual pet cluster; and searching the entity pet hospital based on the pet information set and the object information set.
In a possible example, the adjusting unit 406 is specifically configured to obtain, based on the comment information, a comment value of the second resource configuration; obtaining a similarity value between the first resource configuration and the second resource configuration; determining an optimized resource dimension and a target value of the first resource configuration based on the score value and the similarity value; the first resource configuration is adjusted based on the optimized resource dimension and the target value.
For the detailed process executed by each unit in the resource allocation apparatus 400, refer to the execution steps in the foregoing method embodiments, which are not described herein again.
Referring to fig. 5, fig. 5 is a schematic structural diagram of a computer device according to an embodiment of the present disclosure. The computer device 500 comprises a processor 501, a communication interface 502 and a memory 503. The processor 501, communication interface 502, and memory 503 may be interconnected via the bus 505, or may be otherwise connected. The related functions implemented by the first acquiring unit 401, the second acquiring unit 402, the third acquiring unit 403, the fourth acquiring unit 404, the fifth acquiring unit 405, and the adjusting unit 406 shown in fig. 4 may be implemented by one or more processors 501.
The processor 501 includes one or more processors, for example, one or more Central Processing Units (CPUs), and in the case that the processor 501 is one Central Processing Unit (CPU), the CPU may be a single-core CPU or a multi-core CPU. In the embodiment of the present application, the processor 501 is used to control the computer device 500 to implement the embodiment shown in fig. 3.
The communication interface 502 is used for realizing communication with other devices, for example, if the computer device 500 is a user terminal, the communication interface 502 can realize communication between the user terminal and devices such as a server; if the computer device 500 is a server, the communication interface 502 can enable communication between the server and a device such as a user terminal.
The memory 503 includes, but is not limited to, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), or a portable read-only memory (CD-ROM), and the memory 503 is used for storing relevant instructions and data.
In an embodiment of the application, the memory 503 stores a computer program 504, the computer program 504 comprises program instructions, and the processor 501 is configured to call the program instructions, the program comprises instructions for performing the following steps:
acquiring a pet information set of a virtual pet cluster in a target area and a first resource configuration corresponding to the virtual pet cluster in a virtual pet hospital in the target area;
acquiring a visit information set of an entity pet cluster similar to the virtual pet cluster based on the pet information set;
acquiring the visit demand information of the virtual pet cluster based on the visit information set;
acquiring a matching value between the visit demand information and the visit capacity information corresponding to the first resource configuration;
and if the matching value is smaller than the preset threshold value, adjusting the first resource allocation to increase the resources corresponding to the virtual pet cluster.
In one possible example, in obtaining a set of encounter information for a cluster of physical pets that is similar to the virtual pet cluster based on the set of pet information, the instructions in the program are specifically configured to:
acquiring a label set of the virtual pet cluster based on the pet information set;
determining a similar entity pet cluster of the virtual pet cluster based on the label set;
searching a diagnosis record set of the entity pets in the entity pet cluster;
and processing the visit record set to obtain a visit information set of the entity pet cluster.
In one possible example, the visit information set includes a visit probability and a visit duration corresponding to the visit type, and in terms of processing the visit record set to obtain the visit information set of the entity pet cluster, the instructions in the program are specifically configured to perform the following operations:
dividing the visit record set to obtain a visit record subset corresponding to the visit type;
acquiring the treatment duration corresponding to the treatment type based on the time information in the treatment record subset;
and obtaining the ratio of the number of the pets to be treated corresponding to the treatment type to the number of the pets in the entity pet cluster, and obtaining the treatment probability corresponding to the treatment type.
In one possible example, the visit demand information includes a visit demand duration corresponding to a visit type, and in terms of obtaining the visit demand information of the virtual pet cluster based on the visit information set, the instructions in the program are specifically configured to perform the following operations:
and acquiring the product of the treatment probability corresponding to the treatment type and the treatment duration to obtain the treatment demand duration corresponding to the treatment type.
In one possible example, the first resource configuration includes a sub-resource configuration corresponding to the visit type, and the matching value includes a sub-matching value corresponding to the visit type; in terms of obtaining a matching value between the visit demand information and the visit capability information corresponding to the first resource configuration, the instructions in the program are specifically configured to perform the following operations:
acquiring the length of the visit capacity corresponding to the sub-resource configuration;
and acquiring the ratio of the time required for seeing a doctor to the time of seeing a doctor capability to obtain a sub-matching value corresponding to the type of seeing a doctor.
In one possible example, in adjusting the first resource configuration, the instructions in the program are specifically configured to:
acquiring second resource configuration and comment information corresponding to the entity pet cluster in the entity pet hospital;
and adjusting the first resource configuration based on the second resource configuration and the comment information.
In one possible example, the instructions in the program are further operable to, prior to obtaining the second resource configuration and review information corresponding to the group of physical pets in the physical pet hospital, perform the following operations:
acquiring an object information set corresponding to the virtual pet cluster;
and searching the entity pet hospital based on the pet information set and the object information set.
In one possible example, in adjusting the first resource configuration based on the second resource configuration and the review information, the instructions in the program are specifically configured to:
obtaining a rating value of the second resource configuration based on the comment information;
obtaining a similarity value between the first resource configuration and the second resource configuration;
determining an optimized resource dimension and a target value of the first resource configuration based on the score value and the similarity value;
the first resource configuration is adjusted based on the optimized resource dimension and the target value.
It should be understood that the computer device 500 described in this embodiment of the present application may perform the description of the resource allocation method in the embodiment corresponding to fig. 3, and may also perform the description of the resource allocation apparatus 400 in the embodiment corresponding to fig. 4, which is not described herein again. In addition, the beneficial effects of the same method are not described in detail.
Further, here, it is to be noted that: an embodiment of the present application further provides a computer-readable storage medium, where a computer program executed by the aforementioned resource allocation apparatus is stored in the computer-readable storage medium, and the computer program includes program instructions, and when the processor executes the program instructions, the description of the resource allocation method in the embodiment corresponding to fig. 3 can be performed, so that details are not repeated here. In addition, the beneficial effects of the same method are not described in detail. For technical details not disclosed in embodiments of the computer-readable storage medium referred to in the present application, reference is made to the description of embodiments of the method of the present application. As an example, program instructions may be deployed to be executed on one computing device or on multiple computing devices at one site or distributed across multiple sites and interconnected by a communication network, which may constitute a block chain system.
Further, it should be noted that: embodiments of the present application also provide a computer program product or computer program, which may include computer instructions, which may be stored in a computer-readable storage medium. The processor of the computer device reads the computer instruction from the computer-readable storage medium, and the processor can execute the computer instruction, so that the computer device executes the description of the resource allocation method in the embodiment corresponding to fig. 3, which is described above, and therefore, the description thereof will not be repeated here. In addition, the beneficial effects of the same method are not described in detail. For technical details not disclosed in the computer program product or computer program embodiments referred to in the present application, reference is made to the description of the method embodiments of the present application.
It should be noted that, for simplicity of description, the above-mentioned embodiments of the method are described as a series of acts or combinations, but those skilled in the art should understand that the present application is not limited by the order of acts described, as some steps may be performed in other orders or simultaneously according to the present application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
The steps in the method of the embodiment of the application can be sequentially adjusted, combined and deleted according to actual needs.
The modules in the device can be merged, divided and deleted according to actual needs.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium and can include the processes of the embodiments of the methods described above when the computer program is executed. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The above disclosure is only for the purpose of illustrating the preferred embodiments of the present application and is not to be construed as limiting the scope of the present application, so that the present application is not limited thereto, and all equivalent variations and modifications can be made to the present application.
Claims (10)
1. A method for resource allocation, comprising:
acquiring a pet information set of a virtual pet cluster in a target area and a first resource configuration corresponding to the virtual pet cluster in a virtual pet hospital in the target area;
acquiring a diagnosis information set of an entity pet cluster similar to the virtual pet cluster based on the pet information set;
acquiring the visit demand information of the virtual pet cluster based on the visit information set;
acquiring a matching value between the visit demand information and the visit capacity information corresponding to the first resource configuration;
and if the matching value is smaller than a preset threshold value, adjusting the first resource allocation to increase resources corresponding to the virtual pet cluster.
2. The method of claim 1, wherein said obtaining a set of encounter information for a cluster of physical pets similar to said virtual pet cluster based on said set of pet information comprises:
determining an entity pet cluster similar to the virtual pet cluster based on the pet information set;
searching a diagnosis record set of the entity pets in the entity pet cluster;
and processing the visit record set to obtain a visit information set of the entity pet cluster.
3. The method of claim 2, wherein said visit information set includes a visit probability and a visit duration corresponding to a visit type, and said processing said visit record set to obtain a visit information set for said physical pet cluster comprises:
dividing the visit record set to obtain a visit record subset corresponding to the visit type;
acquiring the visit duration corresponding to the visit type based on the time information in the visit record subset;
and acquiring the ratio of the number of the pets to be treated corresponding to the treatment type to the number of the pets in the entity pet cluster, and acquiring the treatment probability corresponding to the treatment type.
4. The method of claim 3, wherein the encounter demand information includes encounter demand duration corresponding to encounter type, and the obtaining encounter demand information for the virtual pet cluster based on the encounter information set comprises:
acquiring the product of the treatment probability corresponding to the treatment type and the treatment duration to obtain the treatment demand duration corresponding to the treatment type;
the first resource configuration comprises a sub-resource configuration corresponding to the visit type, and the matching value comprises a sub-matching value corresponding to the visit type; the obtaining of the matching value between the visit demand information and the visit capability information corresponding to the first resource configuration includes:
acquiring the length of the visit capability corresponding to the sub-resource configuration;
and acquiring the ratio of the time required for seeing a doctor to the time of seeing a doctor capability to obtain a sub-matching value corresponding to the type of seeing a doctor.
5. The method of any of claims 1-4, wherein the adjusting the first resource configuration comprises:
acquiring second resource configuration and comment information corresponding to the entity pet cluster in the entity pet hospital;
adjusting the first resource configuration based on the second resource configuration and the review information.
6. The method of claim 5, wherein prior to said obtaining a second resource configuration and review information corresponding to said physical pet cluster in a physical pet hospital, said method further comprises:
acquiring an object information set corresponding to the virtual pet cluster;
and searching the entity pet hospital based on the pet information set and the object information set.
7. The method of claim 6, wherein the adjusting the first resource configuration based on the second resource configuration and the review information comprises:
acquiring a rating value of the second resource configuration based on the comment information;
obtaining a similarity value between the first resource configuration and the second resource configuration;
determining an optimized resource dimension and a target value of the first resource configuration based on the scoring value and the similarity value;
adjusting the first resource configuration based on the optimized resource dimension and the target value.
8. A resource allocation apparatus, comprising:
the system comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring a pet information set of a virtual pet cluster in a target area and a first resource configuration corresponding to the virtual pet cluster in a virtual pet hospital in the target area;
a second obtaining unit, configured to obtain a visit information set of an entity pet cluster similar to the virtual pet cluster based on the pet information set;
a third obtaining unit, configured to obtain visit demand information of the virtual pet cluster based on the visit information set;
a fourth obtaining unit, configured to obtain a matching value between the visit demand information and the visit capability information corresponding to the first resource configuration;
and the adjusting unit is used for adjusting the first resource allocation to increase the resources corresponding to the virtual pet cluster if the matching value is smaller than a preset threshold value.
9. A computer device comprising a memory and a processor; the memory is coupled to the processor, the memory configured to store a computer program, the processor configured to invoke the computer program to cause the computer device to perform the method of any of claims 1-7.
10. A computer-readable storage medium, in which a computer program is stored which is adapted to be loaded and executed by a processor, so that a computer device having said processor performs the method of any of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210455871.7A CN114904280B (en) | 2022-04-28 | 2022-04-28 | Resource allocation method, device, equipment and medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210455871.7A CN114904280B (en) | 2022-04-28 | 2022-04-28 | Resource allocation method, device, equipment and medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114904280A true CN114904280A (en) | 2022-08-16 |
| CN114904280B CN114904280B (en) | 2024-08-09 |
Family
ID=82764812
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210455871.7A Active CN114904280B (en) | 2022-04-28 | 2022-04-28 | Resource allocation method, device, equipment and medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114904280B (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140149233A1 (en) * | 2012-11-26 | 2014-05-29 | Jianlin Dai | Interactive system and method of products, services, intelligent information and the like |
| CN107180394A (en) * | 2016-10-11 | 2017-09-19 | 深圳市沃特沃德股份有限公司 | The method for setting up user-association, server and the system entrusted one's child to the care of sb. based on pet |
| CN107731284A (en) * | 2016-08-11 | 2018-02-23 | 李彬 | Medical data sharing method and system |
| CN109343965A (en) * | 2018-10-31 | 2019-02-15 | 北京金山云网络技术有限公司 | Resource adjusting method, device, cloud platform and server |
| CN112509684A (en) * | 2020-12-31 | 2021-03-16 | 曜立科技(北京)有限公司 | Medical resource allocation method and system based on big data |
| CN113571206A (en) * | 2021-07-13 | 2021-10-29 | 何媛媛 | Virtual hospital diagnosis method based on virtual reality |
| CN114287887A (en) * | 2021-12-30 | 2022-04-08 | 新瑞鹏宠物医疗集团有限公司 | Disease diagnosis method, disease diagnosis device, electronic apparatus, and storage medium |
-
2022
- 2022-04-28 CN CN202210455871.7A patent/CN114904280B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140149233A1 (en) * | 2012-11-26 | 2014-05-29 | Jianlin Dai | Interactive system and method of products, services, intelligent information and the like |
| CN107731284A (en) * | 2016-08-11 | 2018-02-23 | 李彬 | Medical data sharing method and system |
| CN107180394A (en) * | 2016-10-11 | 2017-09-19 | 深圳市沃特沃德股份有限公司 | The method for setting up user-association, server and the system entrusted one's child to the care of sb. based on pet |
| CN109343965A (en) * | 2018-10-31 | 2019-02-15 | 北京金山云网络技术有限公司 | Resource adjusting method, device, cloud platform and server |
| CN112509684A (en) * | 2020-12-31 | 2021-03-16 | 曜立科技(北京)有限公司 | Medical resource allocation method and system based on big data |
| CN113571206A (en) * | 2021-07-13 | 2021-10-29 | 何媛媛 | Virtual hospital diagnosis method based on virtual reality |
| CN114287887A (en) * | 2021-12-30 | 2022-04-08 | 新瑞鹏宠物医疗集团有限公司 | Disease diagnosis method, disease diagnosis device, electronic apparatus, and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114904280B (en) | 2024-08-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9361428B2 (en) | System and method for electronically managing medical data files | |
| KR102254419B1 (en) | METHOD AND APPARATUS FOR CURATING COMPANION ANIMAL HEALTH CARE, and system using the same | |
| CN110402570A (en) | Information processing method and system, server, terminal, computer storage medium | |
| CN112148992A (en) | Content pushing method and device, computer equipment and storage medium | |
| CN110443632A (en) | User management method, device, computer equipment and the storage medium of user's portrait | |
| CN111054078B (en) | Object information acquisition method and device | |
| CN112016760A (en) | Combined prediction method and device of multi-dimensional information, computer equipment and medium | |
| US20240315213A1 (en) | Systems and methods for electronic transactions communicating with external pet homing systems | |
| CN110032731A (en) | Business Scope of Enterprise judgment method, device and computer readable storage medium | |
| US20150339602A1 (en) | System and method for modeling health care costs | |
| US20230354782A1 (en) | Systems and methods of integrated platforms for generating a unique identifier for a user-to-pet relationship | |
| CN110428342B (en) | Data restoration method, server, customer service side and storage medium | |
| CN114904280B (en) | Resource allocation method, device, equipment and medium | |
| US20130013328A1 (en) | Systems, methods, and devices for an architecture to support secure massively scalable applications hosted in the cloud and supported and user interfaces | |
| CN111009299A (en) | Similar medicine recommendation method and system, server and medium | |
| CN115271132A (en) | Vaccine reservation method, device, equipment and storage medium | |
| JP2021518625A (en) | Systems and methods for quantifying customer engagement | |
| CN115311100A (en) | Event processing method, device, equipment and storage medium | |
| CN115205775A (en) | Event prompting method, device, equipment and storage medium | |
| CN112037932A (en) | Patient medication behavior intervention method and device, server and storage medium | |
| CN115311099A (en) | Data processing method, device, equipment and storage medium | |
| CN115312165A (en) | Item reservation method, item reservation device, item reservation equipment and storage medium | |
| US20230402141A1 (en) | Systems and methods of integrated platforms for dynamic electronic transactions of petcare data | |
| CN115203531A (en) | Information pushing method, device, equipment and storage medium | |
| CN114887334A (en) | Information pushing method, device, equipment and medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |