CN112270492A - Resource allocation method, device, computer equipment and storage medium - Google Patents
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Abstract
The present disclosure provides a resource allocation method, apparatus, computer device and storage medium, wherein the method comprises: acquiring characteristic information of a user; determining the probability of the user executing a preset behavior based on the characteristic information of the user; screening target users from the users based on the probability of the users executing preset behaviors; and determining the target resources allocated to the target user based on the characteristic information of the target user and/or the probability of the target user executing the preset behavior. According to the method and the device, the target user is screened out by determining the probability of the user executing the preset behavior, different resources are allocated to different users, and therefore the probability of the user executing the preset behavior is improved.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a resource allocation method, an apparatus, a computer device, and a storage medium.
Background
With the rapid development of the internet industry, more and more users use online platforms, and in order to prompt users to perform certain preset behaviors, such as prompting users to consume, the platforms generally dispatch some resources to the users.
However, if only one resource is dispatched to all users, the resource does not have a good promoting effect on all users due to individual differences among different users, and the execution rate of the preset behavior is reduced.
Disclosure of Invention
The embodiment of the disclosure at least provides a resource allocation method, a resource allocation device, a computer device and a storage medium, which allocate different target resources to different users so as to improve the probability of executing a preset behavior by the users.
In a first aspect, an embodiment of the present disclosure provides a resource allocation method, including:
acquiring characteristic information of a user;
determining the probability of the user executing a preset behavior based on the characteristic information of the user;
screening target users from the users based on the probability of the users executing preset behaviors;
and determining the target resources allocated to the target user based on the characteristic information of the target user and/or the probability of the target user executing the preset behavior.
In an optional embodiment, the characteristic information comprises at least one of:
the resource management method comprises the steps of acquiring the type of resources, acquiring the quantity of the resources, reading the type of the resources, reading the quantity of the resources, reading the time length of the resources, reading the frequency of the resources and registering the time length.
In an optional embodiment, the screening target users from the users based on the probability of the users performing the preset action includes:
acquiring a preset probability threshold;
and taking the user with the probability of executing the preset behavior larger than the preset probability threshold value as the target user.
In an optional embodiment, determining the target resource allocated to the target user based on the characteristic information of the target user includes:
acquiring a preset first mapping relation between the characteristic information and resources to be allocated;
and determining the target resource allocated to the target user based on the characteristic information of the target user and the first mapping relation.
In an optional embodiment, determining a target resource allocated to the target user based on a probability that the target user performs a preset action includes:
acquiring a second mapping relation between preset N probability intervals and resources to be allocated;
determining a target probability interval to which the probability of the target user executing the preset behavior belongs based on the probability range information of the probability interval;
and determining the target resource allocated to the target user based on the target probability interval and the second mapping relation.
In an optional implementation manner, determining a target resource allocated to the target user based on the feature information of the target user and the probability of the target user performing a preset action includes:
determining a first resource matched with the characteristic information of the target user;
and screening second resources matched with the probability of executing the preset behavior by the target user from the first resources, and taking the screened second resources as target resources allocated to the target user.
In an optional implementation manner, after determining the target resource allocated to the target user based on the feature information of the target user and/or the probability of the target user performing the preset action, the method further includes:
judging whether the target user accepts the target resource or not;
and under the condition that the target user does not accept the target resource, pushing the target resource to the target user.
In an optional embodiment, in the case that the target user does not accept the target resource, pushing the target resource to the target user includes;
under the condition that the target user does not accept the target resource, judging whether a database contains the target resource or not;
and if the database contains the target resource, pushing the target resource to the target user.
In an optional embodiment, after pushing the target resource to the target user, the method further includes:
and reducing the number of the target resources in the database under the condition that the target users accept the target resources.
In an optional embodiment, the method further comprises: and under the condition that the target user accepts the target resource, sending a prompt message that the target resource is accepted to the target user.
In a second aspect, an embodiment of the present disclosure further provides a resource allocation apparatus, including:
the acquisition module is used for acquiring the characteristic information of the user;
the first determining module is used for determining the probability of executing a preset behavior by the user based on the characteristic information of the user;
the screening module is used for screening target users from the users based on the probability of the users executing the preset behaviors;
and the second determination module is used for determining the target resources allocated to the target user based on the characteristic information of the target user and/or the probability of the target user executing the preset behavior.
In an optional embodiment, the characteristic information comprises at least one of:
the resource management method comprises the steps of acquiring the type of resources, acquiring the quantity of the resources, reading the type of the resources, reading the quantity of the resources, reading the time length of the resources, reading the frequency of the resources and registering the time length.
In an optional implementation manner, the screening module is configured to obtain a preset probability threshold; and taking the user with the probability of executing the preset behavior larger than the preset probability threshold value as the target user.
In an optional implementation manner, the second determining module is configured to obtain a preset target resource matched with the feature information; and determining the target resource allocated to the target user based on the characteristic information of the target user.
In an optional implementation manner, the second determining module is configured to obtain N preset probability intervals and target resources matched with the probability intervals; determining a target probability interval to which the probability of the target user executing the preset behavior belongs; and taking the target resource matched with the target probability interval as the target resource allocated to the target user.
In an optional embodiment, the second determining module is configured to determine a first resource matching the feature information of the target user; and screening second resources matched with the probability of executing the preset behavior by the target user from the first resources, and taking the screened second resources as target resources allocated to the target user.
In an optional embodiment, the method further comprises:
the judging module is used for judging whether the target user accepts the target resource; .
And the pushing module is used for pushing the target resource to the target user under the condition that the target user does not accept the target resource.
In an optional implementation manner, the pushing module is configured to determine whether the database includes the target resource when the target user does not accept the target resource; and if the database contains the target resource, pushing the target resource to the target user.
In an optional embodiment, the pushing module is further configured to reduce the number of the target resource in the database if the target user accepts the target resource.
In an optional embodiment, the method further comprises: and the prompting module is used for sending a prompting message that the target resource is accepted to the target user under the condition that the target user accepts the target resource.
In a third aspect, an embodiment of the present disclosure further provides a computer device, including: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory communicating via the bus when the computer device is running, the machine-readable instructions when executed by the processor performing the steps of the first aspect described above, or any possible implementation of the first aspect.
In a fourth aspect, this disclosed embodiment also provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to perform the steps in the first aspect or any one of the possible implementation manners of the first aspect.
For the description of the effects of the resource allocation apparatus, the computer device and the storage medium, reference is made to the description of the resource allocation method, and details are not repeated here.
According to the resource allocation method, the resource allocation device, the computer equipment and the storage medium, the probability of executing the preset behavior by the user is determined by acquiring the characteristic information of the user, the target user is screened out according to the probability, and finally the target resource is allocated to the target user according to the characteristic information and/or the probability of executing the preset behavior by the user. Compared with the prior art that resource information is allocated to all users in a single mode, the method and the device screen target users by determining the probability of the users executing the preset behaviors and allocate different resources to different users so as to improve the probability of the users executing the preset behaviors.
In order to make the aforementioned objects, features and advantages of the present disclosure more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings required for use in the embodiments will be briefly described below, and the drawings herein incorporated in and forming a part of the specification illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the technical solutions of the present disclosure. It is appreciated that the following drawings depict only certain embodiments of the disclosure and are therefore not to be considered limiting of its scope, for those skilled in the art will be able to derive additional related drawings therefrom without the benefit of the inventive faculty.
Fig. 1 is a flowchart illustrating a resource allocation method provided by an embodiment of the present disclosure;
fig. 2 is a flowchart illustrating a method for resource allocation provided by an embodiment of the present disclosure, in which a target resource allocated to a target user is determined;
FIG. 3 is a flowchart illustrating a method for pushing a target resource to a target user according to an embodiment of the present disclosure;
fig. 4 is a schematic diagram illustrating a resource allocation apparatus provided in an embodiment of the present disclosure;
fig. 5 shows a schematic structural diagram of a computer device provided by an embodiment of the present disclosure.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present disclosure more clear, the technical solutions of the embodiments of the present disclosure will be described clearly and completely with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, not all of the embodiments. The components of the embodiments of the present disclosure, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present disclosure, presented in the figures, is not intended to limit the scope of the claimed disclosure, but is merely representative of selected embodiments of the disclosure. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the disclosure without making creative efforts, shall fall within the protection scope of the disclosure.
Furthermore, the terms "first," "second," and the like in the description and in the claims, and in the drawings described above, in the embodiments of the present disclosure are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein.
Reference herein to "a plurality or a number" means two or more. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship.
Research shows that as more and more users are on line, user differentiation becomes more obvious. If only a single resource is provided for a user, the effect of attracting the user will be different, which may lose attraction for some special users, resulting in a situation where the special users are lost.
Based on the research, the resource allocation method is provided, and specific target resources are allocated to different target users, so that the requirements of the target users are met in a targeted manner, and the user stickiness is promoted.
The above-mentioned drawbacks are the results of the inventor after practical and careful study, and therefore, the discovery process of the above-mentioned problems and the solutions proposed by the present disclosure to the above-mentioned problems should be the contribution of the inventor in the process of the present disclosure.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
To facilitate understanding of the present embodiment, first, a detailed description is given of a resource allocation method disclosed in the embodiments of the present disclosure, where an execution subject of the resource allocation method provided in the embodiments of the present disclosure is generally a computer device with certain computing capability, and the computer device includes, for example: a terminal device, which may be a User Equipment (UE), a mobile device, a User terminal, a cellular phone, a cordless phone, a Personal Digital Assistant (PDA), a handheld device, a computing device, a vehicle mounted device, a wearable device, or a server or other processing device. In some possible implementations, the resource allocation method may be implemented by a processor calling computer readable instructions stored in a memory.
The following describes a resource allocation method provided by the embodiments of the present disclosure by taking an execution subject as a computer device as an example.
Example one
Referring to fig. 1, a flowchart of a resource allocation method provided in the embodiment of the present disclosure is shown, where the method includes steps S101 to S104, where:
s101: and acquiring the characteristic information of the user.
In a possible embodiment, the users refer to known users and potential users who can use the corresponding products, such as students who are using a certain online education APP and people who may use the online education APP in the future, and details thereof are omitted.
In this step, the feature information may include at least one of: the resource management method comprises the steps of acquiring the type of resources, the quantity of the acquired resources, reading the type of the resources, reading the quantity of the resources, reading the time length of the resources, reading the frequency of the resources, registering the time length and the like.
Of course, the characteristic information of the user also includes attributes of the user, such as name, gender, age, grade, contact information, specials, and the like, which can provide assistance for information pushing. For example, through the characteristics, it can be determined that the probability that a student needs a course is very high, and it can be determined that the probability that the student can purchase the course is also higher than that of other students, which is not described herein.
In one possible implementation, the feature information of the user may be obtained from a web page, a landing page embedded in various web pages, an applet, a public number, an APP, and other web page-like platforms, for example, based on an APP platform of the application program.
Example one: and acquiring the characteristic information of the user based on the online learning platform. In specific implementation, the class information and the quantity information of the courses purchased by the user in the platform may be acquired, or the frequency information of the user viewing the number information, the duration information and the courses historically in the platform may be acquired, or the duration registered by the user in the platform may be acquired, so as to determine whether the user is a new user or an old user in the platform, where the administrator may define the duration registered by the user to determine whether the user is a new user or an old user, which is not limited herein.
Example two: and acquiring the characteristic information of the user based on the network information search platform. In the specific implementation, the types of information searched by the user in the platform, the time length for browsing the searched information, the frequency for searching the same information and the like can be obtained.
Example three: and acquiring the characteristic information of the user based on the shopping platform. In specific implementation, the type of the commodity purchased by the user in the platform and the number of the purchased commodities can be obtained, or the type of the commodity historically viewed by the user in the platform, the number of the browsed commodities, the duration of the commodity viewed, the frequency of commodity viewed, or the duration of the commodity viewed registered by the user in the platform can be obtained, so that the user is determined to be a new user or an old user in the platform. The commodity category may include general commodities, luxury goods, and the like, and the division of the specific commodity category may be defined by a manager, which is not limited herein.
S102: and determining the probability of the user executing the preset behavior based on the characteristic information of the user.
In some possible embodiments, the preset behavior is preset according to an actual requirement, and may generally include an additional purchase behavior, a praise behavior, a forward sharing behavior, an attention behavior, an evaluation and review behavior, a participation behavior, and the like, which is not described in detail herein.
In this step, based on the feature information obtained in step S101, the user may be prejudged to execute the preset behavior, and the probability of executing the preset behavior by the user is determined.
Continuing with example one, based on an online learning platform, the preset behavior may include an activity that a user is about to purchase a course. In specific implementation, the user can be determined to be a new user according to the time length of the user registered in the platform, and the probability of the user executing the course purchasing behavior is determined according to the number of courses read by the user; or determining that the user is an old user according to the time length of the user registered in the platform, and determining the probability of the user executing the course purchasing according to the number of the courses browsed by the user. For example, user a is a new user, viewing 20 courses in the platform; the user B is an old user, 20 courses are historically browsed in the platform, and the fact that the probability that the user A performs the course purchasing behavior is larger than that of the user B can be determined.
Continuing with example two, the preset behavior may include a behavior in which the user searches the history information again, based on the network information search platform. During specific implementation, the probability of the user executing the action of searching the similar information can be determined according to the type of the historical search information of the user in the platform; or determining the probability of the user reading the search information again according to the time length of the user reading the search information in the history in the platform; or the probability that the user searches the same information again can be determined according to the frequency of searching the same information in the platform by the user. For example, if the target user searches the class a information 10 times and searches the class B information 3 times in the history of the platform, it can be determined that the probability of the target user performing the search for the class a information is greater than that of the class B information.
Continuing with example three, the pre-set behavior may include behavior that the user is about to purchase a particular good based on the shopping platform. In specific implementation, the probability of executing the commodity purchasing behavior of the user can be determined according to the commodity reading frequency of the user; or according to the time length of the user registering in the platform, determining that the user is a new user or an old user, and determining the probability of the user executing commodity purchase. For example, a user views the item 5 times the same day in the platform; and the user B reads 1 time of the commodity in the same day in the platform, and the probability that the commodity purchasing behavior is executed by the user A is higher than that of the user B.
S103: and screening target users from the users based on the probability of the users executing the preset behaviors.
In specific implementation, a user with a probability of executing a preset action greater than a preset probability threshold may be used as a target user by obtaining the preset probability threshold. And if the preset probability threshold value can be a plurality of, the screened target users correspond to different grades. The ranking of the target users may be divided empirically, or the preset probability threshold may be defined empirically, but is not limited herein.
For example, the target users may be divided into three levels, and users with a probability of executing a preset action greater than 50% and less than 70% are taken as first-level target users; taking users with the probability of executing the preset behaviors more than 70% and less than 90% as secondary target users; and taking users with the probability of executing the preset behaviors more than 90% and less than 100% as three-level target users, wherein the users with the probability of executing the preset behaviors less than 50 are taken as common users.
S104: and determining the target resources allocated to the target users based on the characteristic information of the target users and/or the probability of the target users executing the preset behaviors.
In this step, the target resource may be presented in different platforms in different ways, and specifically, the method may include at least one of the following: information, points, red pack coupons, discount coupons, or means to deliver a complimentary resource, or safflowers for motivational purposes, etc.
In the online learning platform, the target resource can be red packet coupons with different quota values, or coupons for giving lessons, or coupons for free audition courses, or deductions for deducting the fees for learning in the learning process, or learning coins for deducting the fees for learning in the learning process, or small safflowers for encouraging action, and the like. In a network information search platform, the target resource may be information similar to the search information. In the shopping platform, the target resource can be red packet coupons with different quota values, or discount coupons of commodities, or preferential ways of giving gifts, and the like. The coupon may be a platform universal coupon or a universal coupon for a specific target resource, which is not limited herein.
In one possible implementation, the target resource allocated to the target user may be determined based on the characteristic information of the target user. In specific implementation, a first mapping relation between preset characteristic information and resources to be allocated is obtained; and determining the target resource allocated to the target user based on the characteristic information of the target user and the first mapping relation.
Based on the browsing resource frequency, when the browsing resource frequency reaches a preset threshold value, at least one target resource can be matched. In specific implementation, taking the network information search platform as an example, the first mapping relationship between each piece of search information and the similar information resource may be preset, and the similar information resource is used as the target resource allocated to the target user. For example, the similar information may be a work of the same writer, a work of the same director of film, or the like.
Based on the number of the browsing resources, when the number of the acquired resources reaches a preset threshold value, any at least one target resource can be matched. Taking an online learning platform as an example, ten courses can be preset and read, and a 2-element coupon is matched; reading fifteen courses, and matching one 5-element coupon or two 3-element coupons; and viewing twenty courses, one 10-yuan coupon or three 4-yuan coupons can be matched.
For the type of the acquired resource, the number of the acquired resources, the browsing resource type, the browsing resource time and the registration duration, the method for matching the target resource may refer to the browsing resource frequency and the browsing resource number, which is not described herein again.
In another possible implementation, the target resource allocated to the target user may also be determined based on a probability that the target user performs a preset action. In specific implementation, acquiring a second mapping relation between preset N probability intervals and resources to be allocated; determining a target probability interval to which the probability of the target user executing the preset behavior belongs based on the probability range information of the probability interval; and determining the target resource allocated to the target user based on the target probability interval and the second mapping relation.
The predetermined probability interval may include several probability intervals, that is, N is a positive integer.
It should be noted that each probability interval may be matched with a target resource, and in one embodiment, the probability interval may be divided into [0, 1% ] [ 2%, 3% ] [ 4%, 5% ] … … [ 99%, 100% ], and each probability interval may be matched with at least one target resource, for example, the target resource may be a red-pack coupon with different quota values, a 0.01-element coupon corresponds to the [0, 1% ] interval, a 0.02-element coupon corresponds to [ 2%, 3% ], … …, a 10-element coupon corresponds to [ 99%, 100% ].
In one embodiment, the probability intervals may be divided into [0, 50% ] [ 50%, 70% ] [ 70%, 90% ] [ 90%, 100% ], and [ 50%, 70% ] [ 70%, 90% ] [ 90%, 100% ] corresponds to the matching target resource, and [0, 50% ] does not match the target resource.
Based on the condition that part of the probability interval is matched with the target resource, the following exemplary details are provided to determine the target resource allocated to the target user based on the probability of the target user performing the preset action:
example one, the target resource may be a red-pack coupon of different value, 2-tuple coupon corresponding to [ 50%, 70% ] interval, 5-tuple coupon corresponding to [ 70%, 90% ], 10-tuple coupon corresponding to [ 90%, 1000% ].
In the second example, the target resource may also be a piece of information, taking a search literary work as an example, when the target user searches for a certain work of the writer a 10 times, searches for a certain work of the writer B5 times, searches for a certain work of the writer C2 times, the target resource corresponding to the matching [ 50%, 70% ] interval is a random work of the writer C, the target resource corresponding to the matching [ 70%, 90% ] interval is a random work of the writer B, and the target resource corresponding to the matching [ 90%, 100% ] interval is a random work of the writer a.
In another possible implementation, the target resource allocated to the target user may be further determined based on the feature information of the target user and the probability that the target user performs the preset action. In specific implementation, determining a first resource matched with the characteristic information of the target user; and screening second resources matched with the probability of executing the preset action by the target user from the first resources, and taking the screened second resources as target resources distributed to the target user.
Referring to fig. 2, the target resource allocated to the target user may be determined as follows.
S201: and determining a first resource matched with the characteristic information of the target user.
In specific implementation, a first mapping relation between preset characteristic information and resources to be allocated is obtained; and determining the target resource allocated to the target user based on the characteristic information of the target user and the first mapping relation. For a detailed description, reference may be made to the above-mentioned embodiment for determining a target resource allocated to a target user based on feature information of the target user, which is not described herein again.
S202: and screening second resources matched with the probability of executing the preset action by the target user from the first resources, and taking the screened second resources as target resources allocated to the target user.
Based on step S201, in a specific implementation, a second mapping relationship between preset N probability intervals and resources to be allocated is obtained; determining a target probability interval to which the probability of the target user executing the preset behavior belongs based on the probability range information of the probability interval; and determining the target resource allocated to the target user based on the target probability interval and the second mapping relation. For a detailed description, reference may be made to the above-mentioned implementation that determines the target resource allocated to the target user based on the probability of the target user performing the preset behavior, which is not described herein again.
In an example, a target user views fifteen courses, the matched first resource may be one 5-element coupon or two 3-element coupons, and it is determined that the probability of the target user performing a preset action is 85%, the second resource matched with the probability of the target user performing the action of viewing the number of courses is screened from the first resources as one 5-element coupon, and the screened one 5-element coupon is used as the target resource allocated to the target user.
Example two, the target user searches a part of literary works of the writer a, the matched first resource can be the literary works of the writer a, the literary works of the writer B, the literary works of the writer C, and the like, the probability that the target user executes the preset action is judged to be 90%, the second resource matched with the probability that the target user executes the search information action is the literary works of the writer a, and the screened literary works of the writer a are used as the target resource distributed to the target user.
The method for allocating resources, which is provided by the embodiment of the present disclosure, is described in detail through the foregoing steps S101 to S104, and the method determines the probability of executing the preset behavior by the user by obtaining the feature information of the user, screens out the target user according to the probability, and finally allocates the target resources to the target user according to the feature information and/or the probability of executing the preset behavior by the user, so as to meet the demand of the target user in a targeted manner and promote the stickiness of the target user.
Example two
Referring to fig. 3, a flowchart of a method for pushing a target resource to a target user is provided for an embodiment of the present disclosure.
S301: judging whether the target user accepts the target resource, if not, executing the step S302; if so, the routine is ended.
S302: and pushing the target resource to the target user.
S303: and judging whether the database contains the target resource, if so, executing the step S302, and if not, ending the program.
In one embodiment, after pushing the target resource to the target user, the method further comprises: and reducing the number of the target resources in the database under the condition that the target users accept the target resources.
It should be noted that, the database stores target resources, the number of the target resources may correspond to the number of the target users one by one, when a user is added to the platform, the database correspondingly generates target resources that conform to the characteristic information of the user, and when the target user accepts the target resources pushed by the platform, the database correspondingly subtracts the number from the database according to the number of the accepted target resources, so as to complete the update of the number of the target resources in the database.
In specific implementation, when the target user receives the resource, the number of the corresponding target resource in the database is reduced by one until the number of the target resource in the database is zero. For example, based on an online learning platform, a student user with excellent performance can be assigned with a small safflower, and in the case that the student user accepts the small safflower, one small safflower is correspondingly reduced in the database until the small safflower in the system is dispatched. At this point, the database may update other target resources, such as red scarves, etc.
In addition, it should be noted that the target user receives the resource, which may be the target user receiving the resource, and the resource is not used yet; it may also be that the target user has used while drawing resources.
In one embodiment, in the case that the target user accepts the target resource, a prompt message that the target resource is accepted is sent to the target user.
It should be noted that the prompt message may be a mobile terminal short message prompt or a software system message prompt.
It will be understood by those skilled in the art that in the method of the present invention, the order of writing the steps does not imply a strict order of execution and any limitations on the implementation, and the specific order of execution of the steps should be determined by their function and possible inherent logic.
Based on the same inventive concept, a resource allocation apparatus corresponding to the resource allocation method is also provided in the embodiments of the present disclosure, and since the principle of the apparatus in the embodiments of the present disclosure for solving the problem is similar to the resource allocation method described above in the embodiments of the present disclosure, the implementation of the apparatus may refer to the implementation of the method, and repeated details are not described again.
EXAMPLE III
Referring to fig. 4, a schematic diagram of a resource allocation apparatus provided in an embodiment of the present disclosure is shown, where the apparatus includes: an obtaining module 401, a first determining module 402, a screening module 403 and a second determining module 404; wherein,
an obtaining module 401, configured to obtain feature information of a user;
a first determining module 402, configured to determine, based on the feature information of the user, a probability that the user performs a preset behavior;
a screening module 403, configured to screen a target user from the users based on a probability that the user executes a preset behavior;
a second determining module 404, configured to determine, based on the feature information of the target user and/or a probability that the target user performs a preset action, a target resource allocated to the target user.
In one possible embodiment, the characteristic information includes at least one of:
the resource management method comprises the steps of acquiring the type of resources, acquiring the quantity of the resources, reading the type of the resources, reading the quantity of the resources, reading the time length of the resources, reading the frequency of the resources and registering the time length.
In a possible implementation manner, the screening module 403 is configured to obtain a preset probability threshold; and taking the user with the probability of executing the preset behavior larger than the preset probability threshold value as the target user.
In a possible implementation manner, the second determining module 404 is configured to obtain a preset target resource matched with the feature information; and determining the target resource allocated to the target user based on the characteristic information of the target user.
In a possible implementation manner, the second determining module 404 is configured to obtain N preset probability intervals and target resources matched with the probability intervals; determining a target probability interval to which the probability of the target user executing the preset behavior belongs; and taking the target resource matched with the target probability interval as the target resource allocated to the target user.
In a possible implementation manner, the second determining module 404 is configured to determine a first resource matching the feature information of the target user; and screening second resources matched with the probability of executing the preset behavior by the target user from the first resources, and taking the screened second resources as target resources allocated to the target user.
In a possible embodiment, the method further comprises:
a determining module 405, configured to determine whether the target user has accepted the target resource; .
A pushing module 406, configured to push the target resource to the target user when the target user has not accepted the target resource.
In a possible implementation manner, the pushing module 405 is configured to determine whether the database includes the target resource when the target user does not accept the target resource; and if the database contains the target resource, pushing the target resource to the target user.
In a possible implementation, the pushing module 405 is further configured to reduce the amount of the target resource in the database if the target user accepts the target resource.
In a possible embodiment, the method further comprises: a prompt module 407, configured to send a prompt message that the target resource is accepted to the target user when the target user accepts the target resource.
The description of the processing flow of each module in the device and the interaction flow between the modules may refer to the related description in the above method embodiments, and will not be described in detail here.
Example four
Based on the same technical concept, the embodiment of the application also provides computer equipment. Referring to fig. 5, a schematic structural diagram of a computer device provided in an embodiment of the present application includes:
a processor 501, a memory 502, and a bus 503. Wherein the memory 502 stores machine-readable instructions executable by the processor 501, and the processor 501 is configured to execute the machine-readable instructions stored in the memory 502, and when the machine-readable instructions are executed by the processor 501, the processor 501 performs the following steps: s101: acquiring characteristic information of a user; s102: determining the probability of executing a preset behavior by the user based on the characteristic information of the user; s103: screening target users from the users based on the probability of the users executing the preset behaviors; s104: and determining the target resources allocated to the target users based on the characteristic information of the target users and/or the probability of the target users executing the preset behaviors.
The storage 502 includes a memory 5021 and an external storage 5022; the memory 5021 is also referred to as an internal memory and is used for temporarily storing the operation data in the processor 501 and the data exchanged with the external storage 5022 such as a hard disk, the processor 501 exchanges data with the external storage 5022 through the memory 5021, and when the computer device is operated, the processor 501 communicates with the storage 502 through the bus 503, so that the processor 501 executes the instructions mentioned in the above method embodiments.
The embodiments of the present disclosure also provide a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program performs the steps of the resource allocation method in the above method embodiments. The storage medium may be a volatile or non-volatile computer-readable storage medium.
The embodiments of the present disclosure also provide a computer program product, where the computer program product carries a program code, where instructions included in the program code may be used to execute the steps of the xxxx method described in the above method embodiments, which may be referred to in the above method embodiments specifically, and details are not described herein again.
The computer program product may be implemented by hardware, software or a combination thereof. In an alternative embodiment, the computer program product is embodied in a computer storage medium, and in another alternative embodiment, the computer program product is embodied in a Software product, such as a Software Development Kit (SDK), or the like.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the system and the apparatus described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again. In the several embodiments provided in the present disclosure, it should be understood that the disclosed system, apparatus, and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present disclosure may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present disclosure may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present disclosure. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
Finally, it should be noted that: the above-mentioned embodiments are merely specific embodiments of the present disclosure, which are used for illustrating the technical solutions of the present disclosure and not for limiting the same, and the scope of the present disclosure is not limited thereto, and although the present disclosure is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive of the technical solutions described in the foregoing embodiments or equivalent technical features thereof within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present disclosure, and should be construed as being included therein. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.
Claims (13)
1. A method for resource allocation, comprising:
acquiring characteristic information of a user;
determining the probability of the user executing a preset behavior based on the characteristic information of the user;
screening target users from the users based on the probability of the users executing preset behaviors;
and determining the target resources allocated to the target user based on the characteristic information of the target user and/or the probability of the target user executing the preset behavior.
2. The method of claim 1, wherein the characteristic information comprises at least one of:
the resource management method comprises the steps of acquiring the type of resources, acquiring the quantity of the resources, reading the type of the resources, reading the quantity of the resources, reading the time length of the resources, reading the frequency of the resources and registering the time length.
3. The method of claim 1, wherein screening target users from the users based on the probability that the users perform the predetermined action comprises:
acquiring a preset probability threshold;
and taking the user with the probability of executing the preset behavior larger than the preset probability threshold value as the target user.
4. The method of claim 1, wherein determining the target resource allocated to the target user based on the characteristic information of the target user comprises:
acquiring a preset first mapping relation between the characteristic information and resources to be allocated;
and determining the target resource allocated to the target user based on the characteristic information of the target user and the first mapping relation.
5. The method of claim 3, wherein determining the target resource allocated to the target user based on the probability that the target user performs the preset action comprises:
acquiring a second mapping relation between preset N probability intervals and resources to be allocated;
determining a target probability interval to which the probability of the target user executing the preset behavior belongs based on the probability range information of the probability interval;
and determining the target resource allocated to the target user based on the target probability interval and the second mapping relation.
6. The method of claim 1, wherein determining the target resource allocated to the target user based on the feature information of the target user and the probability of the target user performing a preset action comprises:
determining a first resource matched with the characteristic information of the target user;
and screening second resources matched with the probability of executing the preset behavior by the target user from the first resources, and taking the screened second resources as target resources allocated to the target user.
7. The method according to claim 1, wherein after determining the target resource allocated to the target user based on the feature information of the target user and/or the probability of the target user performing a preset action, the method further comprises:
judging whether the target user accepts the target resource or not;
and under the condition that the target user does not accept the target resource, pushing the target resource to the target user.
8. The method of claim 7, wherein in the event that the target user has not accepted the target resource, pushing the target resource to the target user comprises;
under the condition that the target user does not accept the target resource, judging whether a database contains the target resource or not;
and if the database contains the target resource, pushing the target resource to the target user.
9. The method of claim 8, further comprising, after pushing the target resource to the target user:
and reducing the number of the target resources in the database under the condition that the target users accept the target resources.
10. The method according to any one of claims 1 to 9, wherein when the target user accepts the target resource, a message indicating that the target resource is accepted is sent to the target user.
11. A resource allocation apparatus, comprising:
the acquisition module is used for acquiring the characteristic information of the user;
the first determining module is used for determining the probability of executing a preset behavior by the user based on the characteristic information of the user;
the screening module is used for screening target users from the users based on the probability of the users executing the preset behaviors;
and the second determination module is used for determining the target resources allocated to the target user based on the characteristic information of the target user and/or the probability of the target user executing the preset behavior.
12. A computer device, comprising: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory communicating over the bus when a computer device is running, the machine-readable instructions when executed by the processor performing the steps of the resource allocation method according to any one of claims 1 to 10.
13. A computer-readable storage medium, having stored thereon a computer program which, when being executed by a processor, is adapted to carry out the steps of the resource allocation method according to any one of claims 1 to 10.
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