CN113094589A - Intelligent service recommendation method and device - Google Patents
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Abstract
The invention discloses an intelligent service recommendation 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 one or any combination of function operation data, transaction function operation data, setting function operation data, browsing activity operation data, participation activity operation data and browsing information operation data; 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 the APP behavior operation historical data; determining a corresponding service combination set according to the selected situation model; and carrying out intelligent service recommendation according to the service combination set. The invention can intelligently recommend services for the client, simplify the operation of the client and improve the experience of the client.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to an intelligent service recommendation method and device.
Background
Currently, all large banks are built intelligently, but the current service recommendation is a recommendation with a single function, and in fact, the operation of a client often needs continuous service.
Therefore, there is a need for an intelligent service recommendation scheme that can overcome the above problems.
Disclosure of Invention
The embodiment of the invention provides an intelligent service recommendation method, which is used for intelligently recommending services for customers, simplifying customer operation and improving customer experience, and comprises the following steps:
obtaining APP behavior operation data of a client, wherein the APP behavior operation data comprises: inquiring one or any combination of function operation data, transaction function operation data, setting function operation data, browsing activity operation data, participation activity operation data and browsing information operation data;
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 the APP behavior operation historical data;
determining a corresponding service combination set according to the selected situation model;
and carrying out intelligent service recommendation according to the service combination set.
The embodiment of the invention provides an intelligent service recommendation device, which is used for intelligently recommending services for customers, simplifying customer operation and improving customer experience, and comprises the following components:
a first data obtaining module, configured to obtain APP behavior operation data of a client, where the APP behavior operation data includes: inquiring one or any combination of function operation data, transaction function operation data, setting function operation data, browsing activity operation data, participation activity operation data and browsing information operation data;
the model selection module is used for selecting a corresponding situation model from a model base according to the APP behavior operation data, the model base 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 recommendation 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 which is stored on the memory and can run on the processor, wherein the processor realizes the intelligent service recommendation method when executing the computer program.
An embodiment of the present invention further provides a computer-readable storage medium, where a computer program for executing the intelligent service recommendation method is stored in the computer-readable storage medium.
According to the embodiment of the invention, APP behavior operation data of a client is obtained, and the APP behavior operation data comprises: inquiring one or any combination of function operation data, transaction function operation data, setting function operation data, browsing activity operation data, participation activity operation data and browsing information operation data; 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 the APP behavior operation historical data; determining a corresponding service combination set according to the selected situation model; and carrying out intelligent service recommendation according to the service combination set. According to the embodiment of the invention, a plurality of situation models are pre-established according to APP behavior operation historical data to form a model base, after the APP behavior operation data of a client is obtained, the corresponding situation models can be directly selected from the model base, and the corresponding service combination sets are determined so as to carry out intelligent service recommendation, so that the client operation is effectively simplified, and the client experience is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts. In the drawings:
FIG. 1 is a diagram illustrating 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 in an embodiment of the present invention;
FIG. 4 is a block diagram of another intelligent service recommendation device in accordance with an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a computer device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.
In order to intelligently recommend services to a client, simplify client operations, and improve the experience of the client, an embodiment of the present invention provides an intelligent service recommendation method, which, as shown in fig. 1, may include:
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 historical data;
103, determining a corresponding service combination set according to the selected situation model;
and 104, performing intelligent service recommendation according to the service combination set.
As shown in fig. 1, in the embodiment of the present invention, by obtaining APP behavior operation data of a client, the APP behavior operation data includes: inquiring one or any combination of function operation data, transaction function operation data, setting function operation data, browsing activity operation data, participation activity operation data and browsing information operation data; 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 the APP behavior operation historical data; determining a corresponding service combination set according to the selected situation model; and carrying out intelligent service recommendation according to the service combination set. According to the embodiment of the invention, a plurality of situation models are pre-established according to APP behavior operation historical data to form a model base, after the APP behavior operation data of a client is obtained, the corresponding situation models can be directly selected from the model base, and the corresponding service combination sets are determined so as to carry out intelligent service recommendation, so that the client operation is effectively simplified, and the client experience is improved.
In an embodiment, APP behavior operation data of a client is obtained, where the APP behavior operation data includes: inquiring one or any combination of function operation data, transaction function operation data, setting function operation data, browsing activity operation data, participation activity operation data and browsing information operation data.
In the embodiment, according to the APP behavior operation data, a corresponding context model is selected from a model base, the model base comprises a plurality of context models, and each context model is pre-established according to APP behavior operation historical data.
In this embodiment, the context model is pre-established as follows:
obtaining APP behavior operation historical data;
performing correlation analysis on the APP behavior operation historical data;
and establishing a context model according to the result of the association analysis.
In this embodiment, the context model includes: a funding context model and an activity equity context model.
During specific implementation, APP behavior operation historical data of a client on an APP are combined and subjected to correlation analysis, regular action behaviors are extracted by recording the operation behaviors of the client after logging in each time, so that context models are established, each context model corresponds to a service combination set, and the service combination set comprises one or more service types. The context model includes: a funding context model and an activity equity context model. The fund processing situation model corresponds to a series of regular actions contained in APP behavior operation historical data, wherein the regular actions comprise: after the customer clicks and logs in, the customer clicks the account management to inquire the account balance, if the credit card has arrears, the customer clicks the credit card to carry out repayment operation, if the debit card balance exceeds the set amount, the customer clicks the information function to carry out the browsing action of the information, finishes browsing and clicking the financing function, purchases the financing product, clicks the asset management after purchasing the financing product, and checks the current configuration condition. The activity interest situation model corresponds to a series of regular actions contained in APP behavior operation historical data, wherein the regular actions comprise: after the customer clicks and logs in, the customer checks the hot event, clicks and participates in the hot event, obtains a coupon such as a telephone fee recharging coupon, performs the telephone fee recharging function to recharge, then performs inquiry of credit card points, and performs point exchange.
In the embodiment, a corresponding service combination set is determined according to the selected situation 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:
105, obtaining behavior operation feedback data fed back by the client according to the service combination set;
and 106, optimizing the service combination set according to the behavior operation feedback data.
In specific implementation, after the context model is selected, the corresponding service combination set is determined. And then behavior operation feedback data fed back by the client according to the service combination set is obtained, and the service combination set is optimized according to the behavior operation feedback data. And if the customer clicks the account inquiring function after logging in, recommending a service combination set corresponding to the fund processing situation for the customer. And through the feedback of the operation behavior of the customer, a dynamic optimization situation model is carried out, if the amount of money of a debit card exceeds 1 ten thousand after the customer clicks account management, fund transfer is carried out, and if the behavior of the customer exceeds a certain number of times (the number of times can be set), the situation is supplemented into a fund handling situation model, and the optimization of the combined service set is carried out.
Currently, all large banks are built intelligently, but the current service recommendation is a recommendation with a single function, 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 historical data of the client, performs service combination recommendation and contextual response, and helps the client to achieve the maximum requirement by a shortest path.
Based on the same inventive concept, the embodiment of the present invention further provides an intelligent service recommendation apparatus, as described in the following embodiments. Because the principles of solving the problems are similar to those of the intelligent service recommendation method, the implementation of the device can be referred to the implementation of the method, and repeated details are not repeated.
Fig. 3 is a block diagram of an intelligent service recommendation apparatus according to an embodiment of the present invention, and as shown in fig. 3, the apparatus 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 one or any combination of function operation data, transaction function operation data, setting function operation data, browsing activity operation data, participation activity operation data and browsing information operation data;
a model selection module 302, configured to select a corresponding context model from a model library according to the APP behavior operation data, where the model library includes multiple context models, and each context model is pre-established according to APP behavior operation historical data;
a service determining module 303, configured to determine a corresponding service combination set according to the selected context model;
and the intelligent recommendation module 304 is configured to recommend an intelligent service according to the service combination set.
In one embodiment, the context model is pre-established as follows:
obtaining APP behavior operation historical data;
performing correlation analysis on the APP behavior operation historical data;
and establishing a context model according to the result of the association analysis.
In one embodiment, the context model comprises: a funding context model and an activity equity context model.
In one embodiment, as shown in fig. 4, the intelligent service recommendation device further includes:
a second data obtaining module 305, configured to obtain behavior 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 behavior operation feedback data.
In summary, in the embodiments of the present invention, by obtaining APP behavior operation data of a client, the APP behavior operation data includes: inquiring one or any combination of function operation data, transaction function operation data, setting function operation data, browsing activity operation data, participation activity operation data and browsing information operation data; 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 the APP behavior operation historical data; determining a corresponding service combination set according to the selected situation model; and carrying out intelligent service recommendation according to the service combination set. According to the embodiment of the invention, a plurality of situation models are pre-established according to APP behavior operation historical data to form a model base, after the APP behavior operation data of a client is obtained, the corresponding situation models can be directly selected from the model base, and the corresponding service combination sets are determined so as to carry out intelligent service recommendation, so that the client operation is effectively simplified, and the client experience is improved.
Based on the aforementioned inventive concept, as shown in fig. 5, the present invention further provides a computer device 500, which includes a memory 510, a processor 520, and a computer program 530 stored on the memory 510 and executable on the processor 520, wherein the processor 520 executes the computer program 530 to implement the aforementioned intelligent service recommendation method.
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.
As will be appreciated by one skilled in the art, 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 flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams 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 above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. An intelligent service recommendation method, comprising:
obtaining APP behavior operation data of a client, wherein the APP behavior operation data comprises: inquiring one or any combination of function operation data, transaction function operation data, setting function operation data, browsing activity operation data, participation activity operation data and browsing information operation data;
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 the APP behavior operation historical data;
determining a corresponding service combination set according to the selected situation model;
and carrying out intelligent service recommendation according to the service combination set.
2. The intelligent service recommendation method of claim 1, wherein the context model is pre-established as follows:
obtaining APP behavior operation historical data;
performing correlation analysis on the APP behavior operation historical data;
and establishing a context model according to the result of the association analysis.
3. The intelligent service recommendation method of claim 1, wherein the context model comprises: a funding context model and an activity equity context model.
4. The intelligent service recommendation method of claim 1, further comprising:
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.
5. An intelligent service recommendation device, comprising:
a first data obtaining module, configured to obtain APP behavior operation data of a client, where the APP behavior operation data includes: inquiring one or any combination of function operation data, transaction function operation data, setting function operation data, browsing activity operation data, participation activity operation data and browsing information operation data;
the model selection module is used for selecting a corresponding situation model from a model base according to the APP behavior operation data, the model base 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 recommendation module is used for recommending intelligent services according to the service combination set.
6. The intelligent service recommendation apparatus of claim 5, wherein the context model is pre-established as follows:
obtaining APP behavior operation historical data;
performing correlation analysis on the APP behavior operation historical data;
and establishing a context model according to the result of the association analysis.
7. The intelligent service recommendation apparatus of claim 5, wherein the context model comprises: a funding context model and an activity equity context model.
8. The intelligent service recommendation device of claim 5, 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.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 4 when executing the computer program.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program for executing the method of any one of claims 1 to 4.
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