CN113094589B - Intelligent service recommendation method and device - Google Patents
Intelligent service recommendation method and device Download PDFInfo
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Abstract
The invention discloses an intelligent service recommending method and device, which can be used in the technical field of artificial intelligence, wherein the method comprises the following steps: obtaining APP behavior operation data of a client, wherein the APP behavior operation data comprises: inquiring function operation data, transaction function operation data, setting function operation data, browsing activity operation data, participating activity operation data, browsing information operation data or any combination thereof; selecting a corresponding situation model from a model library according to the APP behavior operation data, wherein the model library comprises a plurality of situation models, and each situation model is pre-established according to APP behavior operation historical data; determining a corresponding service combination set according to the selected situation model; and according to the service combination set, intelligent service recommendation is performed. The invention can intelligently recommend service for the clients, simplify the operation of the clients and promote the experience of the clients.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to an intelligent service recommendation method and device.
Background
At present, intelligent construction is performed by each large bank, but the current service recommendation is a single-function recommendation, and in fact, the operation of a client often needs continuous service.
Accordingly, there is a need for an intelligent service recommendation scheme that can overcome the above-described problems.
Disclosure of Invention
The embodiment of the invention provides an intelligent service recommending method, which is used for intelligently recommending services for clients, simplifying the operation of the clients and improving the experience of the clients, and comprises the following steps:
Obtaining APP behavior operation data of a client, wherein the APP behavior operation data comprises: inquiring function operation data, transaction function operation data, setting function operation data, browsing activity operation data, participating activity operation data, browsing information operation data or any combination thereof;
selecting a corresponding situation model from a model library according to the APP behavior operation data, wherein the model library comprises a plurality of situation models, and each situation model is pre-established according to APP behavior operation historical data;
Determining a corresponding service combination set according to the selected situation model;
And according to the service combination set, intelligent service recommendation is performed.
The embodiment of the invention provides an intelligent service recommending device, which is used for intelligently recommending services for clients, simplifying the operation of the clients and improving the experience of the clients, and comprises the following components:
The first data obtaining module is used for obtaining APP behavior operation data of a client, and the APP behavior operation data comprises: inquiring function operation data, transaction function operation data, setting function operation data, browsing activity operation data, participating activity operation data, browsing information operation data or any combination thereof;
The model selection module is used for selecting a corresponding situation model from a model library according to the APP behavior operation data, the model library comprises a plurality of situation models, and each situation model is pre-established according to APP behavior operation historical data;
The service determining module is used for determining a corresponding service combination set according to the selected situation model;
And the intelligent recommending module is used for recommending intelligent services according to the service combination set.
The embodiment of the invention also provides computer equipment, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the intelligent service recommendation method is realized when the processor executes the computer program.
The embodiment of the invention also provides a computer readable storage medium, which stores a computer program for executing the intelligent service recommendation method.
The embodiment of the invention obtains APP behavior operation data of a client, wherein the APP behavior operation data comprises: inquiring function operation data, transaction function operation data, setting function operation data, browsing activity operation data, participating activity operation data, browsing information operation data or any combination thereof; selecting a corresponding situation model from a model library according to the APP behavior operation data, wherein the model library comprises a plurality of situation models, and each situation model is pre-established according to APP behavior operation historical data; determining a corresponding service combination set according to the selected situation model; and according to the service combination set, intelligent service recommendation is performed. According to the embodiment of the invention, a plurality of situation models are pre-established according to the APP behavior operation historical data to form the model library, the corresponding situation models can be directly selected from the model library after the APP behavior operation data of the client is obtained, and the corresponding service combination set is determined so as to conduct intelligent service recommendation, thereby effectively simplifying the client operation and improving the client experience.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. In the drawings:
FIG. 1 is a schematic diagram of an intelligent service recommendation method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of another intelligent service recommendation method according to an embodiment of the present invention;
FIG. 3 is a block diagram of an intelligent service recommendation device according to an embodiment of the present invention;
FIG. 4 is a block diagram of another intelligent service recommendation device according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a computer device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention will be described in further detail with reference to the accompanying drawings. The exemplary embodiments of the present invention and their descriptions herein are for the purpose of explaining the present invention, but are not to be construed as limiting the invention.
In order to intelligently recommend services to clients, simplify the client operation and improve the experience of the clients, an embodiment of the present invention provides an intelligent service recommendation method, as shown in fig. 1, which may include:
Step 101, obtaining APP behavior operation data of a client, wherein the APP behavior operation data comprises: inquiring function operation data, transaction function operation data, setting function operation data, browsing activity operation data, participating activity operation data, browsing information operation data or any combination thereof;
102, selecting a corresponding situation model from a model library according to the APP behavior operation data, wherein the model library comprises a plurality of situation models, and each situation model is pre-established according to APP behavior operation history data;
step 103, determining a corresponding service combination set according to the selected situation model;
and 104, recommending intelligent service according to the service combination set.
As can be seen from fig. 1, the embodiment of the present invention obtains APP behavior operation data of a client, where the APP behavior operation data includes: inquiring function operation data, transaction function operation data, setting function operation data, browsing activity operation data, participating activity operation data, browsing information operation data or any combination thereof; selecting a corresponding situation model from a model library according to the APP behavior operation data, wherein the model library comprises a plurality of situation models, and each situation model is pre-established according to APP behavior operation historical data; determining a corresponding service combination set according to the selected situation model; and according to the service combination set, intelligent service recommendation is performed. According to the embodiment of the invention, a plurality of situation models are pre-established according to the APP behavior operation historical data to form the model library, the corresponding situation models can be directly selected from the model library after the APP behavior operation data of the client is obtained, and the corresponding service combination set is determined so as to conduct intelligent service recommendation, thereby effectively simplifying the client operation and improving the client experience.
In an embodiment, APP behavioural operation data of a client is obtained, the APP behavioural operation data comprising: inquiring function operation data, transaction function operation data, setting function operation data, browsing activity operation data, participating activity operation data, browsing information operation data or any combination thereof.
In an embodiment, according to the APP behavior operation data, a corresponding context model is selected from a model library, wherein the model library includes a plurality of context models, and each context model is pre-established according to APP behavior operation history data.
In this embodiment, a context model is pre-established as follows:
Acquiring APP behavior operation historical data;
Performing association analysis on the APP behavior operation historical data;
and building a situation model according to the result of the association analysis.
In this embodiment, the context model includes: a funding process context model and an activity equity context model.
In the specific implementation, the APP behavior operation history data of the client on the APP is combined and subjected to association analysis, the operation behaviors of the client after logging in each time are recorded, and the regular action behaviors are extracted, so that a situation model is built, each situation model corresponds to a service combination set, and the service combination set comprises one or more service types. The context model includes: a funding process context model and an activity equity context model. The fund processing situation model corresponds to APP behavior operation history data and comprises the following series of regular actions: after the client clicks and logs in, the account management is clicked to inquire the balance of the account, if the credit card has arrears, the credit card is clicked to carry out repayment operation, if the balance of the credit card exceeds the set amount, the information function is clicked to carry out information browsing action, the financial management function is clicked after browsing, the purchase of the financial product is carried out, the asset management is clicked after the purchase of the financial product is completed, and the current configuration condition is checked. The activity rights context model corresponds to APP behavior operation history data and comprises the following series of regular actions: after the client clicks to log in, checking the hot activity, clicking to participate in the hot activity, receiving coupons such as telephone fee recharging coupons, entering a telephone fee recharging function to recharge, inquiring credit card points, and performing point exchange.
In an embodiment, a corresponding service combination set is determined according to the selected context model, and intelligent service recommendation is performed according to the service combination set.
In this embodiment, as shown in fig. 2, the intelligent service recommendation method further includes:
Step 105, obtaining behavior operation feedback data fed back by the customer according to the service combination set;
And 106, optimizing the service combination set according to the behavior operation feedback data.
In particular, after the context model is selected, a corresponding set of service combinations is determined. And then obtaining behavior operation feedback data fed back by the client according to the service combination set, and optimizing the service combination set according to the behavior operation feedback data. If the client clicks the function of inquiring the account after logging in, recommending a service combination set corresponding to the fund processing situation for the client. And the situation model is dynamically optimized through feedback of the operation behaviors of the clients, for example, after the clients click account management, funds are transferred out under the condition that the amount of the debit card exceeds 1 ten thousand, and if the behaviors of the clients exceed a certain number of times (the number of times can be set), the situation is supplemented into the fund disposal situation model, and the optimization of the combined service set is performed.
At present, intelligent construction is performed by each large bank, but the current service recommendation is a single-function recommendation, and in fact, the operation of a client often needs continuous service. Therefore, the embodiment of the invention provides an intelligent service recommendation method, which dynamically recommends a service combination set for a client based on APP behavior operation history data of the client, carries out service combination recommendation and situational response, and helps the client to achieve the maximum demand by a shortest path.
Based on the same inventive concept, the embodiment of the invention also provides an intelligent service recommendation device, as described in the following embodiment. Since the principles of solving the problems are similar to those of the intelligent service recommendation method, the implementation of the device can refer to the implementation of the method, and the repetition is omitted.
Fig. 3 is a structural diagram of an intelligent service recommendation device according to an embodiment of the present invention, and as shown in fig. 3, the device includes:
a first data obtaining module 301, configured to obtain APP behavior operation data of a client, where the APP behavior operation data includes: inquiring function operation data, transaction function operation data, setting function operation data, browsing activity operation data, participating activity operation data, browsing information operation data or any combination thereof;
The model selection module 302 is configured to select a corresponding context model from a model library according to the APP behavior operation data, where the model library includes a plurality of context models, and each context model is pre-established according to APP behavior operation history data;
A service determining module 303, configured to determine a corresponding service combination set according to the selected context model;
And the intelligent recommending module 304 is configured to recommend intelligent services according to the service combination set.
In one embodiment, the context model is pre-established as follows:
Acquiring APP behavior operation historical data;
Performing association analysis on the APP behavior operation historical data;
and building a situation model according to the result of the association analysis.
In one embodiment, the context model comprises: a funding process context model and an activity equity context model.
In one embodiment, as shown in fig. 4, the intelligent service recommendation apparatus further includes:
A second data obtaining module 305, configured to obtain behavioral operation feedback data fed back by the client according to the service combination set;
And the service optimization module 306 is configured to optimize the service combination set according to the behavioral operation feedback data.
In summary, the embodiment of the present invention obtains APP behavior operation data of a client, where the APP behavior operation data includes: inquiring function operation data, transaction function operation data, setting function operation data, browsing activity operation data, participating activity operation data, browsing information operation data or any combination thereof; selecting a corresponding situation model from a model library according to the APP behavior operation data, wherein the model library comprises a plurality of situation models, and each situation model is pre-established according to APP behavior operation historical data; determining a corresponding service combination set according to the selected situation model; and according to the service combination set, intelligent service recommendation is performed. According to the embodiment of the invention, a plurality of situation models are pre-established according to the APP behavior operation historical data to form the model library, the corresponding situation models can be directly selected from the model library after the APP behavior operation data of the client is obtained, and the corresponding service combination set is determined so as to conduct intelligent service recommendation, thereby effectively simplifying the client operation and improving the client experience.
Based on the foregoing inventive concept, as shown in fig. 5, the present invention further proposes a computer device 500, including a memory 510, a processor 520, and a computer program 530 stored on the memory 510 and executable on the processor 520, where the processor 520 implements the foregoing intelligent service recommendation method when executing the computer program 530.
Based on the foregoing inventive concept, the present invention proposes a computer-readable storage medium storing a computer program which, when executed by a processor, implements the foregoing intelligent service recommendation method.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (7)
1. An intelligent service recommendation method, comprising:
Obtaining APP behavior operation data of a client, wherein the APP behavior operation data comprises: inquiring function operation data, transaction function operation data, setting function operation data, browsing activity operation data, participating activity operation data, browsing information operation data or any combination thereof;
Selecting a corresponding situation model from a model library according to the APP behavior operation data, wherein the model library comprises a plurality of situation models, and each situation model is pre-established according to APP behavior operation historical data; the context model comprises: a funding process context model and an activity equity context model; the fund processing situation model corresponds to APP behavior operation history data and comprises the following series of regular actions: after the client clicks and logs in, clicking account management to inquire account balance, if the credit card has arrears, clicking the credit card to carry out repayment operation, if the credit card balance exceeds a set amount, clicking an information function to carry out information browsing action, and after finishing browsing, clicking a financial management function to carry out purchase of a financial product, clicking asset management after purchasing the financial product, and checking the current configuration condition; the activity rights context model corresponds to APP behavior operation history data and comprises the following series of regular actions: after the client clicks to log in, checking the hot activity, clicking to participate in the hot activity, receiving coupons such as telephone fee recharging coupons, performing a telephone fee recharging function to recharge, then inquiring credit card points, and performing point exchange;
Determining a corresponding service combination set according to the selected situation model;
And according to the service combination set, intelligent service recommendation is performed.
2. The intelligent service recommendation method according to claim 1, wherein the context model is pre-established as follows:
Acquiring APP behavior operation historical data;
Performing association analysis on the APP behavior operation historical data;
and building a situation model according to the result of the association analysis.
3. The intelligent service recommendation method according to claim 1, further comprising:
Obtaining behavior operation feedback data fed back by a client according to the service combination set;
And optimizing the service combination set according to the behavior operation feedback data.
4. An intelligent service recommendation device, comprising:
The first data obtaining module is used for obtaining APP behavior operation data of a client, and the APP behavior operation data comprises: inquiring function operation data, transaction function operation data, setting function operation data, browsing activity operation data, participating activity operation data, browsing information operation data or any combination thereof;
The model selection module is used for selecting a corresponding situation model from a model library according to the APP behavior operation data, the model library comprises a plurality of situation models, and each situation model is pre-established according to APP behavior operation historical data; the context model comprises: a funding process context model and an activity equity context model; the fund processing situation model corresponds to APP behavior operation history data and comprises the following series of regular actions: after the client clicks and logs in, clicking account management to inquire account balance, if the credit card has arrears, clicking the credit card to carry out repayment operation, if the credit card balance exceeds a set amount, clicking an information function to carry out information browsing action, and after finishing browsing, clicking a financial management function to carry out purchase of a financial product, clicking asset management after purchasing the financial product, and checking the current configuration condition; the activity rights context model corresponds to APP behavior operation history data and comprises the following series of regular actions: after the client clicks to log in, checking the hot activity, clicking to participate in the hot activity, receiving coupons such as telephone fee recharging coupons, performing a telephone fee recharging function to recharge, then inquiring credit card points, and performing point exchange;
The service determining module is used for determining a corresponding service combination set according to the selected situation model;
And the intelligent recommending module is used for recommending intelligent services according to the service combination set.
5. The intelligent service recommendation apparatus according to claim 4, wherein the context model is pre-established as follows:
Acquiring APP behavior operation historical data;
Performing association analysis on the APP behavior operation historical data;
and building a situation model according to the result of the association analysis.
6. The intelligent service recommendation device according to claim 4, further comprising:
The second data acquisition module is used for acquiring behavior operation feedback data fed back by the client according to the service combination set;
and the service optimization module is used for optimizing the service combination set according to the behavior operation feedback data.
7. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of any of claims 1 to 3 when executing the computer program.
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