CN110135590B - Information processing method, information processing apparatus, information processing medium, and electronic device - Google Patents
Information processing method, information processing apparatus, information processing medium, and electronic device Download PDFInfo
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Abstract
The invention relates to the technical field of data analysis, and discloses an information processing method, an information processing device, an information processing medium and electronic equipment, wherein the method comprises the following steps: when an information processing strategy acquisition request is received, acquiring a value corresponding to an information item in information to be processed and a corresponding attribute value; acquiring a decision tree matched with the information to be processed in the decision tree set according to the information item and the attribute; acquiring leaf nodes according to internal nodes corresponding to the information items and/or the attributes, the values and the attribute values of the information items and decision rules corresponding to the sub-nodes; determining a processing strategy of the information to be processed according to the processing strategy of the leaf node and an actual processing strategy of the historical information to be processed corresponding to the leaf node; and pushing the processing strategy to the user side, and processing the information to be processed according to the actual processing strategy returned by the user side. Under the method, the processing strategy is determined by combining two dimensions of the processing strategy of the leaf node and the actual processing strategy of the corresponding historical information to be processed, so that the information processing efficiency and accuracy are improved.
Description
Technical Field
The present invention relates to the field of data analysis technologies, and in particular, to an information processing method, an information processing apparatus, an information processing medium, and an electronic device.
Background
In machine learning, a decision tree is one of important tools for classifying information or data to establish a mapping relationship between object attributes and object values.
Information as an object also has an attribute value; information can be processed, and information processing strategies such as where and how the information is processed have a certain correlation with the attribute values of the information. Therefore, the decision tree can be used for deciding a corresponding strategy for the information, and the efficient decision of the information processing strategy is realized. In prior art implementations, decision trees for information handling policies are mostly used invariably after they are built.
The prior art has the defects that the decision tree established for the information processing strategy depends heavily on the information data during modeling, and the information data can change dynamically with time; the process of establishing a decision tree, especially a complex decision tree, consumes a lot of resources, which results in that the decision tree cannot be updated at any time, so that the actual decision process of the decision tree often cannot reflect the change of the latest information data, and finally, a decision result may be wrong, so that the efficiency and accuracy of information processing are low.
Disclosure of Invention
The invention provides an information processing method, an information processing device, an information processing medium and electronic equipment, and aims to solve the technical problem that the accuracy of information processing is low due to the fact that a decision tree established aiming at an information processing strategy has a reaction delay on latest information data in the related technology.
According to an aspect of the present application, there is provided an information processing method including:
when an information processing strategy acquisition request aiming at information to be processed from a user side is received, acquiring a value of an information item corresponding to the information item in the information to be processed and an attribute value under an attribute corresponding to an information source identifier of the information to be processed;
acquiring a decision tree matched with the information to be processed from a preset decision tree set according to an information item in the information to be processed and an attribute corresponding to an information source identifier of the information to be processed, wherein the decision tree set comprises at least one decision tree, nodes in the decision tree comprise leaf nodes and internal nodes, each internal node corresponds to the information item in the information to be processed and/or the attribute corresponding to the information source identifier of the information to be processed, a sub node of each internal node corresponds to a decision rule, each leaf node comprises a processing strategy, and each leaf node corresponds to an actual processing strategy of each historical information to be processed;
according to an internal node corresponding to an information item in the information to be processed and/or an attribute corresponding to an information source identifier of the information to be processed, acquiring a leaf node corresponding to the information to be processed in the decision tree by using a value of the information item corresponding to the information item in the information to be processed, an attribute value under the attribute corresponding to the information source identifier of the information to be processed and a decision rule corresponding to a sub-node of the internal node;
determining a processing strategy of the information to be processed according to the acquired processing strategy contained in the leaf node and the acquired actual processing strategy of the historical information to be processed corresponding to the leaf node;
and pushing the determined processing strategy to the user side, and processing the information to be processed according to the actual processing strategy returned by the user side.
According to another aspect of the present application, there is provided an information processing apparatus including:
the information processing method comprises the steps that an obtaining module is configured to obtain values of information items corresponding to the information items in information to be processed and attribute values under attributes corresponding to information source identifiers of the information to be processed when an information processing strategy obtaining request aiming at the information to be processed from a user side is received;
a decision tree acquisition module configured to acquire a decision tree matched with the information to be processed in a preset decision tree set according to an information item in the information to be processed and the attribute corresponding to the information source identifier of the information to be processed, where the decision tree set includes at least one decision tree, nodes in the decision tree include leaf nodes and internal nodes, each internal node corresponds to an information item in the information to be processed and/or an attribute corresponding to the information source identifier of the information to be processed, a sub-node of each internal node corresponds to a decision rule, each leaf node includes a processing policy, and the leaf node corresponds to an actual processing policy of each historical information to be processed;
a leaf node obtaining module configured to obtain, according to an internal node corresponding to an information item in the information to be processed and/or an attribute corresponding to an information source identifier of the information to be processed, a leaf node corresponding to the information to be processed in the decision tree by using a value of the information item corresponding to the information item in the information to be processed, an attribute value under the attribute corresponding to the information source identifier of the information to be processed, and a decision rule corresponding to a sub-node of the internal node;
the processing strategy determining module is configured to determine a processing strategy of the information to be processed according to the acquired processing strategy contained in the leaf node and an actual processing strategy of historical information to be processed corresponding to the acquired leaf node;
and the pushing processing module is configured to push the determined processing strategy to the user side and process the information to be processed according to the actual processing strategy returned by the user side.
According to another aspect of the present application, there is provided a computer readable program medium storing computer program instructions which, when executed by a computer, cause the computer to perform the method as previously described.
According to another aspect of the present application, there is provided an electronic device including:
a processor;
a memory having computer readable instructions stored thereon which, when executed by the processor, implement the method as previously described.
The technical scheme provided by the embodiment of the invention can have the following beneficial effects:
the information processing method provided by the invention comprises the following steps: when an information processing strategy acquisition request aiming at information to be processed from a user side is received, acquiring the value of an information item corresponding to the information item in the information to be processed and the attribute value under the attribute corresponding to the information source identification of the information to be processed; acquiring a decision tree matched with information to be processed from a preset decision tree set according to information items in the information to be processed and attributes corresponding to information source identifications of the information to be processed, wherein the decision tree set comprises at least one decision tree, nodes in the decision tree comprise leaf nodes and internal nodes, each internal node corresponds to an information item in the information to be processed and/or an attribute corresponding to an information source identification of the information to be processed, sub-nodes of each internal node correspond to decision rules, each leaf node comprises a processing strategy, and the leaf nodes correspond to actual processing strategies of each historical information to be processed; according to an internal node corresponding to an information item in the information to be processed and/or an attribute corresponding to an information source identifier of the information to be processed, acquiring a leaf node corresponding to the information to be processed in the decision tree by using a value of the information item corresponding to the information item in the information to be processed, an attribute value under the attribute corresponding to the information source identifier of the information to be processed and a decision rule corresponding to a sub-node of the internal node; determining a processing strategy of the information to be processed according to the acquired processing strategy contained in the leaf node and the acquired actual processing strategy of the historical information to be processed corresponding to the leaf node; and pushing the determined processing strategy to the user side, and processing the information to be processed according to the actual processing strategy returned by the user side.
According to the method, the decision tree matched with the information to be processed is automatically obtained from the preset decision tree set, and then after the corresponding leaf node is obtained from the decision tree, the processing strategy in the leaf node and the corresponding actual processing strategy of the historical information to be processed are combined to finally determine the processing strategy of the information to be processed, so that the actual processing strategy which is also corresponding to the same leaf node can be reflected in the finally determined processing strategy in time historically, the accuracy of the pushed information processing strategy can be improved, and the efficiency and the accuracy of information processing can be improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
FIG. 1 is a system architecture diagram illustrating a method of information processing in accordance with an exemplary embodiment;
FIG. 2 is a flow diagram illustrating an information processing method according to an exemplary embodiment;
FIG. 3 is a flowchart illustrating steps prior to step 230 according to one embodiment illustrated in a corresponding embodiment in FIG. 2;
FIG. 4 is a schematic diagram illustrating logical relationships among nodes of a decision tree in accordance with an illustrative embodiment;
FIG. 5 is a schematic diagram illustrating logical relationships in a decision tree node according to another exemplary embodiment;
FIG. 6 is a flowchart illustrating details of step 240 according to one embodiment illustrated in a corresponding embodiment of FIG. 2;
FIG. 7 is a flowchart illustrating details of step 242 according to one embodiment illustrated in a corresponding embodiment in FIG. 6;
FIG. 8 is a block diagram illustrating an information processing apparatus in accordance with an exemplary embodiment;
FIG. 9 is a block diagram illustrating an example of an electronic device for implementing the above-described information processing method in accordance with one illustrative embodiment;
fig. 10 is a diagram illustrating a computer-readable storage medium for implementing the above-described information processing method according to an exemplary embodiment.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. The following description refers to the accompanying drawings in which the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the invention, as detailed in the appended claims.
Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities.
The present disclosure first provides an information processing method. The information referred to herein may be various types of information, such as production data information, business process information, or technical material information, and it should be understood that the information exists in the form of data at the digital device and may be represented in the form of a file. The information processing refers to a process of processing information to obtain an information processing result, wherein the obtained information processing result is implicit or another new information. The implementation terminal of the present disclosure may be any device having computing, processing, and communication functions, such as a portable mobile device, e.g., a smart phone, a tablet computer, a notebook computer, etc., or a fixed device, e.g., a server, a computer device, a field terminal, a desktop computer, a workstation, etc. The implementation terminal of the present invention may communicate with the external devices in a wired or wireless manner, which may include a combination of hardware, software or firmware.
Fig. 1 is a system architecture diagram illustrating an information processing method according to an example embodiment. As shown in fig. 1, the system comprises a server 110 and a computer terminal 120, wherein the server 110 is a terminal implementing the information processing method provided in the embodiment, and the computer terminal 120 interacts with the server 110 through a communication link. The computer terminal 120 is a terminal used by a user, the user can send a request for obtaining an information processing policy to the server 110 through the computer terminal 120, the server 110 can return a corresponding information processing policy to the computer terminal 120 for recommendation according to the request, and finally the server 110 can process information to be processed according to the actual processing policy returned by the user side, where the information processing policy may be a method or a scheme related to the information processing process, such as how to process the information and where to process the information.
FIG. 2 is a flow chart illustrating an information processing method according to an exemplary embodiment. As shown in fig. 2, the method comprises the following steps:
The information processing policy acquisition request is a network request for instructing the local terminal to start determining and pushing the information processing policy, and may be a request established based on various network protocols, such as a request established by a POST or GET method under the HTTP protocol.
The information item is unit information in the information to be processed, for example, the information item can be the minimum unit which can be processed in the information to be processed, the value of the information item is the actual content of the information item, and the information item is the name or the summary of the actual content; the information source identifier is an identifier capable of uniquely representing the identity of a provider of information to be processed, and may be, for example, an identifier in various forms such as an IP Address, an MAC Address (Media Access Control Address), a mobile phone number, an email Address, an account number, and the like of a terminal; an attribute is unit information similar to an information item, and differs from the information item in that the attribute corresponds to an information source identifier, and the attribute value is the actual content of the attribute.
For example, for the information to be processed, the information to be processed may be a development document, the information item in the information to be processed is a configuration item, such as application configuration, database configuration, log configuration, and the like, and the value of the information item is the actual content configured for the configuration item such as application configuration, database configuration, log configuration, and the like; for the information source identifier and the corresponding attribute, the information source identifier may be a mailbox address of the developer, the corresponding attribute may be an age of the developer, a department code number of the developer, a development time of the development object, and the like, and then the attribute value may be "34", "CDG", "2018.9-2019.3".
In one embodiment, the information item and the corresponding information item value and the attribute and attribute value are stored in a mapping table, respectively, the information item and the attribute are keys (keys) in the mapping table, respectively, and the information item value and the attribute value corresponding to the information item are values (values) in the mapping table, respectively.
In one embodiment, the information processing policy obtaining request includes information to be processed, and the information to be processed is used to obtain a value of an information item corresponding to the information item in the information to be processed and an attribute value under an attribute corresponding to an information source identifier of the information to be processed.
In one embodiment, the information processing policy obtaining request includes an identifier of information to be processed, and before receiving the information processing policy obtaining request for the information to be processed from the user side, the method includes: receiving information to be processed from a user side and an identifier of the information to be processed, and correspondingly storing the information to be processed and the identifier of the information to be processed; the acquiring a value of an information item corresponding to an information item in the information to be processed and an attribute value under an attribute corresponding to an information source identifier of the information to be processed includes: acquiring the information to be processed which is stored corresponding to the identifier of the information to be processed contained in the information processing strategy acquisition request; and acquiring the value of an information item corresponding to the information item in the information to be processed and the attribute value under the attribute corresponding to the information source identifier of the information to be processed according to the information to be processed.
In one embodiment, the obtaining the value of the information item corresponding to the information item in the information to be processed and the attribute value under the attribute corresponding to the information source identifier of the information to be processed includes: for each information item included in the information to be processed, acquiring the value of the information item corresponding to the information item; and acquiring an attribute value under the attribute corresponding to the information source identifier of the information to be processed by utilizing a preset information source identifier and attribute corresponding relation table.
In one embodiment, the steps included prior to step 230 are as shown in FIG. 3. Fig. 3 is a flow chart illustrating steps prior to step 230 according to one embodiment illustrated in a corresponding embodiment of fig. 2. As shown in fig. 3, the method comprises the following steps:
In one embodiment, the client is installed with a client, a tab option in the form of a button control is displayed on a page of the client, and a user clicks the tab option to send a tab to the home terminal.
In one embodiment, the user terminal receives the label input by the user through a text box input mode, and then the label is sent to the local terminal.
Step 220, returning the tag list related to the tag to the user side, so that the user of the user side can select the tag.
The tag list comprises a plurality of tags, each tag in the tag list corresponds to at least one piece of information to be processed, and the user completes input of the information to be processed by selecting the tag at the user terminal, so that an information processing strategy acquisition request aiming at the information to be processed is formed and sent to the local terminal.
In one embodiment, the information processing policy obtaining request for the information to be processed is formed by adding the input information to be processed to the information processing policy obtaining request.
In one embodiment, all information to be processed is manually tagged.
The method and the device have the advantages that a way for quickly selecting the information to be processed is provided for the user in a label mode, and the acquisition efficiency of the information to be processed is improved.
The decision tree set comprises at least one decision tree, nodes in the decision tree comprise leaf nodes and internal nodes, each internal node corresponds to an information item in information to be processed and/or an attribute corresponding to an information source identifier of the information to be processed, a sub node of each internal node corresponds to a decision rule, each leaf node comprises a processing strategy, and the leaf node corresponds to an actual processing strategy of each historical information to be processed.
A decision tree is a tree structure for classification, including nodes and paths between nodes. When the decision tree is stored, the decision tree is stored according to a tree-shaped data structure. The specific storage manner of the decision tree may be various, for example, the decision tree may be stored by using a pickle module in Python language. Each internal node corresponds to an information item in the information to be processed and/or an attribute corresponding to the information source identifier of the information to be processed, that is, each internal node makes a decision or judges on the corresponding attribute corresponding to the information item in the information to be processed and/or the information source identifier of the information to be processed. The sub-node of the internal node corresponds to the decision rule means that if the internal node has a corresponding sub-node, the information to be processed can conform to the decision rule corresponding to the sub-node of the internal node, that is, the decision rule corresponding to the sub-node of the internal node is a result of making a decision or judging the internal node.
FIG. 4 is a diagram illustrating logical relationships in a decision tree node, according to an exemplary embodiment. The decision tree is used for deciding whether a task needs to be switched to a standby system or not according to the to-be-processed information containing the target system load rate, the target system load, the target system availability and the like. As shown in fig. 4, the decision tree includes 3 internal nodes and 4 leaf nodes. The target system load rate is greater than the load rate threshold, the target system load is greater than the load threshold, and the target system availability is reduced, wherein the information item in the information to be processed corresponding to each internal node and/or the attribute corresponding to the information source identifier of the information to be processed are/is provided, the corresponding ellipse containing the information item and/or the attribute is the internal node, the other ellipses containing the task switching to the backup system and the task not switching to the backup system are leaf nodes, and the task switching to the backup system and the task not switching to the backup system are processing strategies contained by the leaf nodes; each arrow shown in the embodiment of fig. 4, i.e. the information on the path from each internal node to its child node, is the decision rule corresponding to the child node of the internal node, for example, the decision rule corresponding to the child node containing "target system load greater than load threshold" is that "target system load rate is less than or equal to load rate threshold", and the decision rule corresponding to the child node containing "target system availability reduction" is that "target system load is less than or equal to load threshold".
Each internal node is branched into sub-nodes because the information to be processed conforms to the corresponding decision rule.
In one embodiment, the decision tree set includes decision trees, and different information to be processed may correspond to different decision trees.
In one embodiment, each historical pending information corresponding to a leaf node and the actual processing policy for that historical pending information are stored in the leaf node.
In one embodiment, each leaf node includes a leaf node identifier, and each historical to-be-processed information corresponding to each leaf node and the actual processing policy of each historical to-be-processed information are stored outside the leaf node, such as in a historical to-be-processed information database, corresponding to the leaf node identifier of the leaf node.
In one embodiment, the steps of step 240 are embodied as shown in FIG. 6. Fig. 6 is a flowchart illustrating details of step 240 according to an embodiment illustrated in a corresponding embodiment of fig. 2, and as shown in fig. 6, includes the following steps:
In one embodiment, the information items and/or attributes corresponding to the internal nodes of the decision tree are stored in the internal nodes of the decision tree, and the information items and/or attributes corresponding to the internal nodes of each decision tree are obtained by reading each decision tree in the preset decision tree set.
In one embodiment, each decision tree further includes a root node, where the root node stores therein an identifier of the decision tree, a preset database correspondingly stores therein the identifier of the decision tree and a corresponding information item and/or attribute corresponding to an internal node of the decision tree, and the information item and/or attribute corresponding to the internal node of the decision tree is obtained in the preset database by obtaining the identifier of the decision tree in the root node of each decision tree.
When a decision tree has internal nodes, and there are internal nodes corresponding to the attributes corresponding to the information item in each piece of information to be processed and the information source identifier of each piece of information to be processed, the decision tree can be used to process the information to be processed, and at this time, the decision tree can be considered to be matched with the information to be processed.
In one embodiment, the detailed steps of step 242 are illustrated in FIG. 7. Fig. 7 is a flowchart illustrating details of step 242 according to an embodiment shown in fig. 6, where in the embodiment of fig. 7, the root node of each decision tree in the preset decision tree set includes a usage log of the decision tree, and the method includes the following steps:
As described above, when the internal node in a decision tree corresponds to each information item in the to-be-processed information or the attribute corresponding to the information source identifier of the to-be-processed information, the decision tree can be used to perform information processing policy decision on the to-be-processed information.
In one embodiment, a counter is provided in the implementation terminal of the present disclosure, and the number of candidate decision trees can be calculated by using the counter.
The usage log is a log that records usage of the decision tree.
In one embodiment, the usage log of each decision tree includes historical usage times of the decision tree, and the obtaining of the decision tree matching the information to be processed based on the usage log of each candidate decision tree includes: sequencing the candidate decision trees from large to small according to the use times in the use logs of the candidate decision trees; and acquiring the candidate decision tree with the minimum sequence number as the decision tree matched with the information to be processed.
Since the smaller the ranking sequence number is, the more the number of times of use of the candidate decision tree is, which indicates to a certain extent that the candidate decision tree is more likely to be selected and used, the present embodiment has an advantage in that, when the number of candidate decision trees is large, the accuracy of the obtained decision tree matched with the information to be processed is improved to a certain extent by ranking the candidate decision trees based on the number of times of use in the usage log and obtaining the candidate decision tree with the largest number of times of use according to the ranked sequence number.
Referring to FIG. 5, a schematic diagram of the logical relationships in a decision tree node is shown. Fig. 5 shows a decision tree for making a processing strategy whether claims should be settled or not for policy information under a vehicle insurance claim settlement scenario. The contents of the "historical risk occurrence record times", "claim amount", and the like are all information items in the information to be processed corresponding to each internal node, the "sex male" is an attribute corresponding to an information source identifier of the information to be processed, a corresponding ellipse containing the information item and/or the attribute is the internal node, all nodes except the internal node, for example, nodes containing information processing strategies of "claim" and "no claim", are leaf nodes, and an arrow pointing to a child node of the internal node is a decision rule.
For example, for a policy information containing information items such as "history record number of times of occurrence is equal to 6", "claim amount is equal to 35 ten thousand", "history violation number of regulations is equal to 18", and corresponding values of the information items, it is first determined that the policy information conforms to a decision rule that the history record number of times of occurrence is less than or equal to 8 and greater than or equal to 5, then a node corresponding to the "history record number of occurrence" points to a node corresponding to the "claim amount", then it is determined that the policy information conforms to a decision rule that the claim amount is greater than or equal to 20 ten thousand yuan, then the node corresponding to the "claim amount" points to a leaf node containing "no claim", and finally an information processing policy of "no claim" is obtained.
In one embodiment, the specific steps of step 260 include: determining the number of actual processing strategies consistent with the processing strategies contained in the leaf node in the actual processing strategies of the historical information to be processed corresponding to the obtained leaf node; when the number is larger than or equal to a preset processing strategy number threshold value, taking the acquired processing strategy contained in the leaf node as the processing strategy of the information to be processed; and when the number is smaller than a preset processing strategy number threshold value, taking the actual processing strategy with the maximum number in the actual processing strategies of the historical information to be processed corresponding to the acquired leaf node as the processing strategy of the information to be processed.
The larger the number is, the higher the possibility that the processing strategy made by using the decision tree is consistent with the actually adopted processing strategy for such information is, which indicates that the decision tree can well make the decision of the information processing strategy for the information to be processed, so that the embodiment has the advantage of improving the accuracy of the acquired processing strategy of the information to be processed.
In one embodiment, the specific steps of step 260 include: determining the ratio of the number of processing strategies consistent with the processing strategies contained in the leaf node in the actual processing strategies of the historical information to be processed corresponding to the obtained leaf node to the number of all actual processing strategies of the historical information to be processed corresponding to the obtained leaf node; when the ratio is larger than or equal to a preset ratio threshold, taking the processing strategy contained in the acquired leaf node as the processing strategy of the information to be processed; and when the ratio is smaller than a preset ratio threshold, taking the actual processing strategy with the largest number in the actual processing strategies of the historical information to be processed corresponding to the acquired leaf node as the processing strategy of the information to be processed.
Since the number of actual processing policies of the historical information to be processed corresponding to the acquired leaf node varies, the number of actual processing policies that are identical to the processing policy included in the leaf node among the actual processing policies of the historical information to be processed corresponding to the acquired leaf node does not accurately reflect a case where the processing policy made by the decision tree is identical to the processing policy actually adopted historically for similar information to be processed, so this embodiment is advantageous in that it determines which processing policy to select as the processing policy of the information to be processed by using a relative ratio, thereby taking a relative quantitative relationship between the processing policy identical to the processing policy included in the leaf node and all the actual processing policies of the historical information to be processed corresponding to the acquired leaf node among the actual processing policies of the historical information to be processed corresponding to the acquired leaf node as the acquisition processing policy The judgment basis of the strategy improves the reliability and the accuracy of the acquired processing strategy.
In one embodiment, determining a ratio of the number of processing strategies that are consistent with the processing strategies included in the leaf node among the actual processing strategies of the historical to-be-processed information corresponding to the obtained leaf node to the number of all actual processing strategies of the historical to-be-processed information corresponding to the obtained leaf node includes:
obtaining a difference value between the current time and the establishment time of the decision tree;
determining a correction factor using the difference value based on the following equation:
wherein x is the difference between the current time and the setup time of the decision tree, xTIs a time difference threshold, V is a correction factor;
and determining the product of the ratio of the number of processing strategies which are consistent with the processing strategies contained in the leaf node in the actual processing strategies of the historical information to be processed corresponding to the obtained leaf node and the number of all actual processing strategies of the historical information to be processed corresponding to the obtained leaf node and the correction coefficient as a ratio.
The larger the difference between the current time and the establishment time of the decision tree is, the longer the establishment time of the decision tree is, that is, the more the decision tree lags behind the current actual decision situation, and at this time, the more the processing strategy directly obtained by using the decision tree should not be used as the finally obtained processing strategy. In this embodiment, the ratio is corrected by using a formula, so that when the difference between the current time and the setup time of the decision tree is greater than a time difference threshold and the difference is greater, the obtained ratio is smaller, but the reduction amplitude is reduced as the difference increases, that is, the ratio is smaller, so that the obtained ratio is easier to be smaller than a predetermined ratio threshold, and thus when the difference between the current time and the setup time of the decision tree is greater than the time difference threshold, the actual processing policy with the largest number in the actual processing policies of the historical to-be-processed information corresponding to the obtained leaf node is more likely to be selected as the finally-obtained processing policy, which improves the accuracy of the processing policy obtained for the to-be-processed information to a certain extent.
The step of processing the information to be processed according to the actual processing strategy returned by the user side means that corresponding actions are executed on the objects related to the information to be processed according to the actual processing strategy returned by the user side. For example, as for the processing policy in the schematic diagram shown in the embodiment of fig. 5, the manner of processing the information is to carry out claim settlement or not.
In one embodiment, the determined processing policy is pushed to the user side by an HTML file, and an actual processing policy returned by the user side is received through a form of a page.
In summary, according to the information processing method provided in the embodiment of fig. 2, the processing policy of the information to be processed is determined by simultaneously combining the two dimensions of the processing policy in the leaf node of the decision tree and the corresponding actual processing policy of the historical information to be processed, so that the processing policy actually adopted for the same and similar information to be processed historically can be reflected in the finally obtained decision result of the processing policy in time, the accuracy of the pushed information processing policy can be improved, and the efficiency and accuracy of information processing can be improved.
Fig. 8 is a block diagram illustrating an information processing apparatus according to an example embodiment. As shown in fig. 8, the apparatus 800 includes:
the obtaining module 810 is configured to, when receiving an information processing policy obtaining request for information to be processed from a user side, obtain a value of an information item corresponding to the information item in the information to be processed and an attribute value under an attribute corresponding to an information source identifier of the information to be processed.
A decision tree obtaining module 820 configured to obtain a decision tree matched with the information to be processed in a preset decision tree set according to the information item in the information to be processed and the attribute corresponding to the information source identifier of the information to be processed, where the decision tree set includes at least one decision tree, nodes in the decision tree include leaf nodes and internal nodes, each internal node corresponds to an information item in the information to be processed and/or an attribute corresponding to an information source identifier of the information to be processed, a child node of each internal node corresponds to a decision rule, each leaf node includes a processing policy, and the leaf node corresponds to an actual processing policy of each historical information to be processed.
A leaf node obtaining module 830, configured to obtain, according to an internal node corresponding to an information item in the information to be processed and/or an attribute corresponding to an information source identifier of the information to be processed, a leaf node corresponding to the information to be processed in the decision tree by using a value of the information item corresponding to the information item in the information to be processed, an attribute value under the attribute corresponding to the information source identifier of the information to be processed, and a decision rule corresponding to a sub-node of the internal node.
A processing policy determining module 840 configured to determine a processing policy of the information to be processed according to the obtained processing policy included in the leaf node and an actual processing policy of the historical information to be processed corresponding to the obtained leaf node.
A pushing processing module 850 configured to push the determined processing policy to the user side, and process the information to be processed according to the actual processing policy returned by the user side.
According to a third aspect of the present disclosure, there is also provided an electronic device capable of implementing the above method.
As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or program product. Thus, various aspects of the invention may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.
An electronic device 900 according to this embodiment of the invention is described below with reference to fig. 9. The electronic device 900 shown in fig. 9 is only an example and should not bring any limitations to the function and scope of use of the embodiments of the present invention.
As shown in fig. 9, the electronic device 900 is embodied in the form of a general purpose computing device. Components of electronic device 900 may include, but are not limited to: the at least one processing unit 910, the at least one memory unit 920, and a bus 930 that couples various system components including the memory unit 920 and the processing unit 910.
Wherein the storage unit stores program code that can be executed by the processing unit 910, such that the processing unit 910 performs the steps according to various exemplary embodiments of the present invention described in the section "example methods" above in this specification.
The storage unit 920 may include readable media in the form of volatile memory units, such as a random access memory unit (RAM)921 and/or a cache memory unit 922, and may further include a read only memory unit (ROM) 923.
The electronic device 900 may also communicate with one or more external devices 1100 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 900, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 900 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interface 950. Also, the electronic device 900 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet) via the network adapter 960. As shown, the network adapter 960 communicates with the other modules of the electronic device 900 via the bus 930. It should be appreciated that although not shown, other hardware and/or software modules may be used in conjunction with the electronic device 900, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, to name a few.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.
According to a fourth aspect of the present disclosure, there is also provided a computer-readable storage medium having stored thereon a program product capable of implementing the above-mentioned method of the present specification. In some possible embodiments, aspects of the invention may also be implemented in the form of a program product comprising program code means for causing a terminal device to carry out the steps according to various exemplary embodiments of the invention described in the above section "exemplary methods" of the present description, when said program product is run on the terminal device.
Referring to fig. 10, a program product 1000 for implementing the above method according to an embodiment of the present invention is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited in this regard and, in the present document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
Furthermore, the above-described figures are merely schematic illustrations of processes involved in methods according to exemplary embodiments of the invention, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.
It will be understood that the invention is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.
Claims (9)
1. An information processing method, characterized in that the method comprises:
when an information processing strategy acquisition request aiming at information to be processed from a user side is received, acquiring the value of an information item corresponding to the information item in the information to be processed and the attribute value under the attribute corresponding to the information source identifier of the information to be processed;
acquiring a decision tree matched with the information to be processed from a preset decision tree set according to an information item in the information to be processed and an attribute corresponding to an information source identifier of the information to be processed, wherein the decision tree set comprises at least one decision tree, nodes in the decision tree comprise leaf nodes and internal nodes, each internal node corresponds to the information item in the information to be processed and/or the attribute corresponding to the information source identifier of the information to be processed, a sub node of each internal node corresponds to a decision rule, each leaf node comprises a processing strategy, and each leaf node corresponds to an actual processing strategy of each historical information to be processed;
according to an internal node corresponding to an information item in the information to be processed and/or an attribute corresponding to an information source identifier of the information to be processed, acquiring a leaf node corresponding to the information to be processed in the decision tree by using a value of the information item corresponding to the information item in the information to be processed, an attribute value under the attribute corresponding to the information source identifier of the information to be processed and a decision rule corresponding to a sub-node of the internal node;
determining the ratio of the number of processing strategies consistent with the processing strategies contained in the leaf node in the actual processing strategies of the historical information to be processed corresponding to the obtained leaf node to the number of all actual processing strategies of the historical information to be processed corresponding to the obtained leaf node;
when the ratio is larger than or equal to a preset ratio threshold, taking the processing strategy contained in the acquired leaf node as the processing strategy of the information to be processed;
when the ratio is smaller than a preset ratio threshold, taking the actual processing strategy with the largest number in the actual processing strategies of the historical information to be processed corresponding to the acquired leaf node as the processing strategy of the information to be processed;
and pushing the determined processing strategy to the user side, and processing the information to be processed according to the actual processing strategy returned by the user side.
2. The method according to claim 1, wherein the obtaining a decision tree matching the information to be processed in a preset decision tree set according to the information item in the information to be processed and the attribute corresponding to the information source identifier of the information to be processed comprises:
aiming at each decision tree in the preset decision tree set, acquiring information items and/or attributes corresponding to internal nodes of the decision tree;
and acquiring the decision tree with the internal nodes corresponding to the information item in each piece of information to be processed and the attribute corresponding to the information source identifier of each piece of information to be processed respectively according to the information item and/or the attribute corresponding to the internal node of each decision tree, and taking the decision tree with the internal node corresponding to the information item in each piece of information to be processed and the attribute corresponding to the information source identifier of the piece of information to be processed as the decision tree matched with the piece of information to be processed.
3. The method according to claim 2, wherein a root node of each decision tree in the preset decision tree set contains a usage log of the decision tree, and the obtaining, as the decision tree matching the information to be processed, the decision tree having a corresponding internal node corresponding to each information item in the information to be processed and each attribute corresponding to an information source identifier of the information to be processed according to an information item and/or attribute corresponding to the internal node of each decision tree comprises:
obtaining a decision tree with internal nodes corresponding to the information item in each piece of information to be processed and the attribute corresponding to the information source identifier of each piece of information to be processed respectively according to the information item and/or the attribute corresponding to the internal node of each decision tree, and taking the decision tree with the internal node corresponding to the information item in each piece of information to be processed and the attribute corresponding to the information source identifier of the piece of information to be processed as a candidate decision tree;
when the number of the candidate decision trees is equal to 1, taking the candidate decision trees as decision trees matched with the information to be processed;
and when the number of the candidate decision trees is more than 1, obtaining the decision tree matched with the information to be processed based on the use log of each candidate decision tree.
4. The method of claim 3, wherein the usage log of each decision tree includes historical usage times of the decision tree, and when the number of candidate decision trees is greater than 1, obtaining a decision tree matching the information to be processed based on the usage log of each candidate decision tree comprises:
sequencing the candidate decision trees from large to small according to the use times in the use logs of the candidate decision trees;
and acquiring the candidate decision tree with the minimum sequence number as the decision tree matched with the information to be processed.
5. The method according to claim 1, wherein before when receiving an information processing policy obtaining request for information to be processed from a user side, obtaining a value of an information item corresponding to the information item in the information to be processed and an attribute value under an attribute corresponding to an information source identifier of the information to be processed, the method comprises:
receiving a label sent by a user side;
and returning a tag list related to the tags to the user side so as to facilitate the user of the user side to select, wherein the tag list comprises a plurality of tags, each tag in the tag list corresponds to at least one piece of information to be processed, and the user completes the input of the information to be processed by selecting the tags at the user side, so as to form an information processing strategy acquisition request aiming at the information to be processed and send the information processing strategy acquisition request to the local side.
6. The method of claim 1, wherein determining a ratio of a number of processing policies that are consistent with the processing policies included in the leaf node among the actual processing policies of the historical to-be-processed information corresponding to the obtained leaf node to a number of all actual processing policies of the historical to-be-processed information corresponding to the obtained leaf node comprises:
obtaining a difference value between the current time and the establishment time of the decision tree;
determining a correction factor using the difference value based on the following equation:
wherein x is the difference between the current time and the setup time of the decision tree, xTIs a time difference threshold, V is a correction factor;
and determining the product of the ratio of the number of processing strategies which are consistent with the processing strategies contained in the leaf node in the actual processing strategies of the historical information to be processed corresponding to the obtained leaf node and the number of all actual processing strategies of the historical information to be processed corresponding to the obtained leaf node and the correction coefficient as a ratio.
7. An information processing apparatus characterized in that the apparatus comprises:
the information processing method comprises the steps that an obtaining module is configured to obtain values of information items corresponding to the information items in information to be processed and attribute values under attributes corresponding to information source identifiers of the information to be processed when an information processing strategy obtaining request aiming at the information to be processed from a user side is received;
a decision tree acquisition module configured to acquire a decision tree matched with the information to be processed in a preset decision tree set according to an information item in the information to be processed and the attribute corresponding to the information source identifier of the information to be processed, where the decision tree set includes at least one decision tree, nodes in the decision tree include leaf nodes and internal nodes, each internal node corresponds to an information item in the information to be processed and/or an attribute corresponding to the information source identifier of the information to be processed, a sub-node of each internal node corresponds to a decision rule, each leaf node includes a processing policy, and the leaf node corresponds to an actual processing policy of each historical information to be processed;
a leaf node obtaining module configured to obtain, according to an internal node corresponding to an information item in the information to be processed and/or an attribute corresponding to an information source identifier of the information to be processed, a leaf node corresponding to the information to be processed in the decision tree by using a value of the information item corresponding to the information item in the information to be processed, an attribute value under the attribute corresponding to the information source identifier of the information to be processed, and a decision rule corresponding to a sub-node of the internal node;
a processing policy determining module configured to determine a ratio of the number of processing policies that are consistent with the processing policies included in the leaf node among the actual processing policies of the historical information to be processed corresponding to the obtained leaf node to the number of all actual processing policies of the historical information to be processed corresponding to the obtained leaf node; when the ratio is larger than or equal to a preset ratio threshold, taking the processing strategy contained in the acquired leaf node as the processing strategy of the information to be processed; when the ratio is smaller than a preset ratio threshold, taking the actual processing strategy with the largest number in the actual processing strategies of the historical information to be processed corresponding to the acquired leaf node as the processing strategy of the information to be processed;
and the pushing processing module is configured to push the determined processing strategy to the user side and process the information to be processed according to the actual processing strategy returned by the user side.
8. A computer-readable program medium, characterized in that it stores computer program instructions which, when executed by a computer, cause the computer to perform the method according to any one of claims 1 to 6.
9. An electronic device, characterized in that the electronic device comprises:
a processor;
a memory having stored thereon computer readable instructions which, when executed by the processor, implement the method of any of claims 1 to 6.
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