CN115757966A - Product recommendation method and device, computer-readable storage medium and electronic equipment - Google Patents

Abstract

The invention discloses a product recommendation method, a product recommendation device, a computer readable storage medium and electronic equipment. Relating to the field of financial science and technology or other fields, the method comprises the following steps: acquiring service information generated when a target object transacts a service to be handled on a target service platform, wherein the target object is an object of which at least object information is registered on a target financial platform; determining at least one product to be recommended from a plurality of products provided by the target financial platform based on the business information; and displaying at least one product to be recommended on a target service platform, wherein the target service platform is used for recommending at least one product to be recommended to a target object. The invention solves the technical problem of low recommendation accuracy caused by indiscriminate recommendation of financial products to users in the prior art.

Description

Product recommendation method and device, computer-readable storage medium and electronic equipment

Technical Field

The invention relates to the field of financial technology or other fields, in particular to a product recommendation method and device, a computer-readable storage medium and electronic equipment.

Background

Traditional product recommendation of financial institutions mostly develops around self channels and self product mainlines, the self channels of finance are limited, and scenes (opportunities) that customers directly need services provided by the financial institutions are few, so that the financial institutions usually adopt a mode of 'first entering into the main' and 'taking products as the center' to indiscriminately recommend newly released financial products to the customers, so that the problems of low recommendation accuracy and high recommendation cost are caused, the recommendation success rate is low, and the customer experience is poor easily caused.

In view of the above problems, no effective solution has been proposed.

Disclosure of Invention

The embodiment of the invention provides a product recommendation method and device, a computer-readable storage medium and electronic equipment, which are used for at least solving the technical problem of low recommendation accuracy caused by indiscriminate recommendation of financial products to users in the prior art.

According to an aspect of an embodiment of the present invention, there is provided a product recommendation method applied to a target financial platform, including: acquiring service information generated when a target object transacts a service to be handled on a target service platform, wherein the target object is an object of which at least object information is registered on a target financial platform; determining at least one product to be recommended from a plurality of products provided by the target financial platform based on the business information; and displaying at least one product to be recommended on a target service platform, wherein the target service platform is used for recommending the at least one product to be recommended to a target object.

Further, the product recommendation method further comprises the following steps: determining the service type of the service to be handled based on the service information; and determining at least one product to be recommended from a plurality of products provided by the target financial platform according to the service category of the service to be handled.

Further, the product recommendation method further comprises the following steps: determining at least one initial product to be recommended corresponding to the service category of the service to be handled from a plurality of products according to the service category of the service to be handled; and determining at least one product to be recommended from at least one initial product to be recommended according to the association degree between the service category of the service to be handled and each initial product to be recommended.

Further, the product recommendation method further comprises the following steps: acquiring object information of a target object stored in a target financial platform; and determining at least one product to be recommended from a plurality of products provided by the target financial platform based on the service category of the service to be handled and the object information of the target object according to the preset corresponding relation between the service category and the product.

Further, the product recommendation method further comprises: after at least one product to be recommended is displayed on a target service platform, determining the use information of each product to be recommended by a target object, wherein the use information is used for representing whether the target object holds the current product to be recommended before the target object finishes handling the service to be recommended; and adjusting the degree of association between the service category of the service to be handled and the product to be recommended based on the use information.

Further, the product recommendation method further comprises the following steps: if the target object purchases the current product to be recommended, updating the target association degree from the first association degree to a second association degree, wherein the target association degree represents the association degree between the service category of the service to be handled and the current product to be recommended, and the second association degree is higher than the first association degree; and if the target object does not purchase the current product to be recommended, updating the target association degree from the first association degree to a third association degree, wherein the first association degree is higher than the third association degree.

Further, the product recommendation method further comprises: after at least one product to be recommended is displayed on the target service platform, responding to the selection operation of a target object on the target service platform on the at least one product to be recommended, and displaying a target purchasing interface provided by the target financial platform through the target service platform, wherein the target purchasing interface is an interface corresponding to the product to be recommended selected by the target object; detecting whether a target object triggers a purchase operation on a target purchase interface; and if the purchase operation triggered by the target object on the target purchase interface is detected, recording the purchase information of the target object.

According to another aspect of the embodiments of the present invention, there is also provided a product recommendation apparatus, including: the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring service information generated when a target object transacts a service to be handled on a target service platform, and the target object is an object of which at least object information is registered on a target financial platform; the system comprises a first determination module, a recommendation module and a recommendation module, wherein the first determination module is used for determining at least one product to be recommended from a plurality of products provided by a target financial platform based on business information; the display module is used for displaying at least one product to be recommended on the target service platform, wherein the target service platform is used for recommending at least one product to be recommended to the target object.

According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to execute the above-mentioned product recommendation method when running.

According to another aspect of the embodiments of the present invention, there is also provided an electronic device, including one or more processors; a memory for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement a method for executing a program, wherein the program is arranged to perform the above-mentioned product recommendation method when executed.

In the embodiment of the invention, when the target object transacts the business, the product is recommended for the target object according to the business requirement of the target object, the business information generated when the target object transacts the business to be handled on the target business platform is obtained, and then at least one product to be recommended is determined from a plurality of products provided by the target financial platform based on the business information, so that at least one product to be recommended is displayed on the target business platform. The target object is an object of which at least object information is registered in the target financial platform, and the target service platform is used for recommending at least one product to be recommended to the target object.

In the process, the product recommended to the target object is determined based on the service information generated when the target object handles the service to be handled on the target service platform, and the product recommended to the target object is determined according to the current service requirement of the target object, so that the recommendation accuracy and timeliness of the product recommended to the target object can be effectively improved, the problem of low recommendation accuracy caused by indiscriminate recommendation of financial products to users in the related technology is solved, and the problem of poor recommendation timeliness caused by continuous change of the requirements of the users when the products are recommended to the users according to the user figures of the target object is solved. In addition, by recommending products to the target object on the target service platform for handling the agency service of the target object, the timeliness of recommendation can be further improved, and a user can conveniently and quickly know the products to be recommended.

Therefore, the proposal provided by the application achieves the aim of recommending products for the target object according to the service requirements of the target object when the target object transacts services, thereby realizing the technical effect of improving the accuracy of recommending the products to the target object and further solving the technical problem of low accuracy of recommending financial products to users without difference in the prior art.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:

FIG. 1 is a schematic diagram of an alternative target financial platform according to an embodiment of the present invention;

FIG. 2 is a schematic diagram of an alternative product recommendation method according to an embodiment of the present invention;

FIG. 3 is a schematic diagram of an alternative service and product convergence module, according to an embodiment of the invention;

FIG. 4 is a schematic diagram of an alternative traffic analysis module according to an embodiment of the present invention;

FIG. 5 is a schematic view of an alternative maintenance module according to an embodiment of the present invention;

FIG. 6 is a schematic diagram of an alternative recommendation module in accordance with embodiments of the present invention;

FIG. 7 is a schematic diagram of an alternative product recommendation method according to an embodiment of the present invention;

FIG. 8 is a schematic view of an alternative product recommendation device according to an embodiment of the present invention;

FIG. 9 is a schematic diagram of an alternative electronic device according to embodiments of the present invention.

Detailed Description

In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in other sequences than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

It should be noted that the product recommendation method, the product recommendation device, the computer-readable storage medium, and the electronic device provided by the present disclosure may be used in the field of financial technology, and may also be used in any field other than the field of financial technology.

It should be noted that relevant information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for presentation, analyzed data, etc.) referred to in the present disclosure are information and data that are authorized by the user or sufficiently authorized by various parties. For example, an interface is provided between the system and the relevant user or organization, before obtaining the relevant information, an obtaining request needs to be sent to the user or organization through the interface, and after receiving the consent information fed back by the user or organization, the relevant information is obtained.

Example 1

In accordance with an embodiment of the present invention, there is provided an embodiment of a method for product recommendation, it should be noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than here.

In this embodiment, as shown in fig. 1, the aforementioned product recommendation method is executed by taking a target financial platform as an execution subject, where the target financial platform is a platform for providing financial products to users, and the target financial platform includes a service and product fusion module 1, a service analysis module 2, a maintenance module 3, and a recommendation module 4. The system comprises a service and product fusion module 1, a partner service module 5, a service analysis module 2, a recommendation module 4, a service and product analysis module 2, a maintenance module 3 and the recommendation module 4, wherein the service and product fusion module 1 is connected with the partner service module 5 through the Internet, the service and product fusion module 1 is also connected with the service analysis module 2 and the recommendation module 4, and the service analysis module 2 is connected with the service and product fusion module 1, the maintenance module 3 and the recommendation module 4; the maintenance module 3 is connected with the recommendation module 4; the recommendation module 4 is connected with the service and product fusion module 1, the service analysis module 2 and the maintenance module 3.

Fig. 2 is a schematic diagram of an alternative product recommendation method according to an embodiment of the present invention, as shown in fig. 2, the method is applied to a target financial platform, and includes the following steps:

step S201, service information generated when a target object transacts a to-be-handled service on a target service platform is obtained, where the target object is an object for which at least object information is registered on a target financial platform.

Optionally, as shown in fig. 3, the service and product convergence module 1 includes a service information receiving unit 11. Before acquiring service information generated when a target object handles a service to be handled on a target service platform, a service handling request of the service to be handled, which is sent by the target service platform response object, is first obtained, and at this time, the target service platform can first determine whether the target object is an object of which the object information is registered on a target financial platform, that is, the target service platform first determines whether the target object is a common client of the target service platform and the target financial platform, and if the target object is a common client of the target service platform and the target financial platform, the target service platform can send the service information generated when the target object handles the service to be handled to a service information receiving unit 11 for the service information receiving unit 11 to obtain. The target service platform may handle services for a target object, the target service platform is the partner service module 5, and the partner service module 5 may be a self-service terminal in an authority, a computer, or a related application on various mobile devices. The service information may include identification information corresponding to a service scenario handled by the target object, information related to the service scenario (e.g., service handling time, service background, service usage, service abstract, service content, etc.), and information such as name, contact information, and the like of the target object. The identification information may be a scene type ID, and the service scene of the service handled by the target object may be tax, social security, water and electricity, property, and the like.

It should be noted that, by acquiring the service information generated when the target object transacts the to-be-handled service on the target service platform, the current service requirement of the target object can be determined timely and accurately.

Step S202, at least one product to be recommended is determined from a plurality of products provided by the target financial platform based on the business information.

In step S202, as shown in fig. 4, the service analysis module 2 includes the service information analysis unit 22. The service information analysis unit 22 may obtain the service information through the service information receiving unit 11, and then determine the service category of the service to be handled based on the service information, for example, when the service scene in the service information is a tax scene, the service information analysis unit 22 may determine the service category of the service to be handled as tax payment or export tax refund based on the service scene and information related to the service scene, and for example, when the service scene in the service information is a vendor registration scene, the service information analysis unit 22 may determine the service category of the service to be handled as a vendor registration license or a fund check based on the service scene and information related to the service scene.

Further, after the service information analysis unit 22 determines the service category of the service to be handled, the service information analysis unit 22 may determine at least one product to be recommended from a plurality of products provided by the target financial platform based on a preset correspondence between the service category and the product. Optionally, the service information analysis unit 22 may use all products corresponding to the service category as products to be recommended, or may screen a part of products from all products corresponding to the service category according to a preset screening rule, as products to be recommended. The products provided by the target financial platform can be related financing products, financing products and the like, for example, when the business category is export tax refund, the products to be recommended can be tax refund investment financing products and the like.

It should be noted that the product recommended to the target object is determined based on the service information generated when the target object handles the service to be handled on the target service platform, so that the product recommended to the target object is determined according to the current service requirement of the target object, the timeliness and the recommendation accuracy of the product recommended to the target object can be effectively improved, the problem of low recommendation accuracy caused by indiscriminate recommendation of financial products to users in the related art is solved, and the problem of poor recommendation timeliness caused by continuous change of the requirements of the users when the products are recommended to the users according to the user representation of the target object is solved.

Step S203, at least one product to be recommended is displayed on a target service platform, wherein the target service platform is used for recommending at least one product to be recommended to a target object.

Optionally, as shown in fig. 3, the service and product convergence module 1 further includes a recommendation instruction receiving unit 13 and a service output unit 14. The recommendation instruction receiving unit 13 is configured to obtain a product list of at least one product to be recommended and send the product list of the at least one product to be recommended to the service output unit 14, the service output unit 14 is configured to be interconnected with the partner service module 5, and the service output unit 14 may package a function for displaying and purchasing the product to be recommended, and open the function to the partner service module 5 in an API interface manner, so that the function is called by the partner service module 5, so that the at least one product to be recommended may be displayed on the target service platform.

It should be noted that, by recommending products to the target object on the target service platform for transacting the agency service by the target object, the timeliness of recommendation can be further improved, and a user can conveniently and quickly know the products to be recommended.

Based on the schemes defined in steps S201 to S203, it can be known that, in the embodiment of the present invention, in a manner that a product is recommended for a target object according to a service requirement of the target object when the target object handles a service, by obtaining service information generated when the target object handles a service to be handled on a target service platform, and then determining at least one product to be recommended from a plurality of products provided by a target financial platform based on the service information, at least one product to be recommended is displayed on the target service platform. The target object is an object of which the object information is registered at least in the target financial platform, and the target service platform is used for recommending at least one product to be recommended to the target object.

It is easy to notice that in the above process, the product recommended to the target object is determined based on the service information generated when the target object handles the service to be handled on the target service platform, so that the product recommended to the target object is determined according to the current service requirement of the target object, the recommendation accuracy and timeliness of the product recommended to the target object can be effectively improved, the problem of low recommendation accuracy caused by indiscriminate recommendation of financial products to users in the related art is avoided, and the problem of poor recommendation timeliness caused by continuous change of the user requirement when the product is recommended to the user according to the user representation of the target object is avoided. In addition, by recommending products to the target object on the target service platform for handling the agency service of the target object, the timeliness of recommendation can be further improved, and a user can conveniently and quickly know the products to be recommended.

Therefore, the proposal provided by the application achieves the aim of recommending products for the target object according to the service requirements of the target object when the target object transacts services, thereby realizing the technical effect of improving the accuracy of recommending the products to the target object and further solving the technical problem of low accuracy of recommending financial products to users without difference in the prior art.

In an alternative embodiment, in the process of determining at least one product to be recommended from a plurality of products provided by the target financial platform based on the service information, the target financial platform may determine a service category of the service to be handled based on the service information, and then determine at least one product to be recommended from the plurality of products provided by the target financial platform according to the service category of the service to be handled.

Optionally, as shown in fig. 3, the service and product convergence module 1 further includes a notification unit 12, and as shown in fig. 4, the service analysis module 2 further includes a service information conversion unit 21 and a service information analysis unit 22. After the service information receiving unit 11 obtains the service information, the service information receiving unit 11 may send the service information to the service information conversion unit 21 through the notification unit 12, and the service information conversion unit 21 converts the format of the service information into a format readable by the service information analysis unit 22.

Further, the service information conversion unit 21 may send the format-converted service information to the service information analysis unit 22. After the service information analysis unit 22 obtains the format-converted service information, the service scene and the service category corresponding to the service information may be queried through the maintenance module 3. The service category may be understood as a specific classification in a service scenario.

Optionally, as shown in fig. 5, the maintenance module 3 includes a service scenario maintenance unit 31 and a service class maintenance unit 32. The service scene maintenance unit 31 is configured to set and maintain service scene parameters, including identification information corresponding to a service scene, service providing service for the service scene, a service scene location, and the like, where the service scene includes tax, social security, water and electricity, property, and the like. The service category maintenance unit 32 is configured to set and maintain parameters such as service categories and service functions provided by each service scenario, for example, service categories such as tax payment declaration and tax return application provided in a tax scenario.

In the process that the service information analysis unit 22 queries the service scene and the service category corresponding to the service information through the maintenance module 3, the service information analysis unit 22 may determine, through the service scene maintenance unit 31, a correspondence between identification information corresponding to the service scene and the service scene, so as to determine the service scene of the service to be handled based on the service information of the service to be handled, and further, the service information analysis unit 22 may determine, through the service category maintenance unit 32, a correspondence between information related to the service scene and the service category, so as to determine the service category of the service to be handled based on the service information of the service to be handled.

Further, as shown in fig. 4, the service analysis module 2 further includes a service information analysis result pushing unit 23, and as shown in fig. 6, the recommendation module 4 includes a result receiving unit 41, a recommendation triggering unit 42, an inquiry triggering unit 43, and a matching result receiving unit 44. After determining the service type of the service to be handled, the service information analysis unit 22 may send the service information and the corresponding service scenario and service type to the result receiving unit 41 through the service information analysis result pushing unit 23, and the result receiving unit 41 forwards the service information and the corresponding service scenario and service type to the query triggering unit 43, so as to query the maintenance module 3 for the product to be recommended through the query triggering unit 43, and then obtain the query result through the matching result receiving unit 44, where the recommendation triggering unit 42 is configured to send the query result obtained by the matching result receiving unit 44 to the recommendation instruction receiving unit 13.

Optionally, as shown in fig. 5, the maintenance module 3 further includes a relationship maintenance unit 33, a relationship storage unit 34, a relationship query unit 35, and a result feedback unit 36, where the relationship maintenance unit 33 is configured to set and maintain a corresponding relationship and an association degree between a service category and a product, where one service category may correspond to multiple products, and one product may also be applicable to multiple service categories. The relationship saving unit 34 is configured to save the correspondence and the degree of association between the service category and the product, so as to be used by the relationship querying unit 35. The relationship query unit 35 is configured to provide a query service according to the query request sent by the query triggering unit 43, and the result feedback unit 36 is configured to feed back a query result, that is, a product list of the product to be recommended, to the matching result receiving unit 44.

It should be noted that the product to be recommended is determined according to the service category of the service to be handled, so that the product to be recommended is accurately determined.

In an optional embodiment, in the process of determining at least one product to be recommended from a plurality of products provided by the target financial platform according to the service category of the service to be handled, the target financial platform may determine at least one initial product to be recommended from the plurality of products, which corresponds to the service category of the service to be handled, according to the service category of the service to be handled, so that the at least one product to be recommended is determined from the at least one initial product to be recommended according to the degree of association between the service category of the service to be handled and each initial product to be recommended.

Optionally, the relationship query unit 35 may first determine at least one initial product to be recommended corresponding to the service category of the service to be handled based on the corresponding relationship between the service category and the product stored in the relationship storage unit 34, and then determine at least one product to be recommended from the at least one initial product to be recommended based on the degree of association between the service category and the product stored in the relationship storage unit 34.

Specifically, in the process of determining at least one to-be-recommended product from at least one initial to-be-recommended product, the relationship querying unit 35 may determine, as to-be-recommended products, the initial to-be-recommended products with the top N degrees of association, where N is a positive integer greater than 0.

It should be noted that at least one product to be recommended is determined by combining the degree of association between the service category and the product, so that further screening of the initial product to be recommended is realized, and the recommendation accuracy is further improved.

In an optional embodiment, in the process of determining at least one product to be recommended from a plurality of products provided by the target financial platform according to the service category of the service to be handled, the target financial platform may obtain object information of a target object stored in the target financial platform, and then determine at least one product to be recommended from the plurality of products provided by the target financial platform based on the service category of the service to be handled and the object information of the target object according to a preset correspondence between the service category and the product.

Optionally, the relationship saving unit 34 may save object information registered by the target object on the target financial platform, where the object information at least includes identity information of the target object and financial service information of a service transacted on the target financial platform, and the relationship querying unit 35 may determine information such as an asset and a historical requirement of the target object according to the object information of the target object, so as to determine at least one initial product to be recommended from the multiple products according to a service category of the service to be transacted, and then determine the product to be recommended from the at least one initial product to be recommended by combining the information such as the asset and the historical requirement of the target object. For example, if the service category of the to-do service is deposit, when a user has a large amount of deposit, the investment product is determined as the to-be-recommended product from the initial to-be-recommended products, and when the deposit of the user is small, the credit product is determined as the to-be-recommended product from the initial to-be-recommended products.

It should be noted that, by combining the personal information of the user, more targeted recommendation to different users can be realized. Thereby further improving the recommendation effect.

In an optional embodiment, after at least one product to be recommended is displayed on the target service platform, the target financial platform may determine usage information of the target object for each product to be recommended, so as to adjust a degree of association between a service category of the service to be handled and the product to be recommended based on the usage information, where the usage information is used for characterizing whether the target object holds the current product to be recommended before the service to be handled is completed.

Optionally, as shown in fig. 3, the service and product fusion module 1 further includes a usage information receiving unit 15 and a usage information forwarding unit 16, and as shown in fig. 6, the recommendation module 4 further includes a recommendation result receiving unit 45 and a relationship optimization triggering unit 46. The usage information receiving unit 15 may obtain the recommendation result through the partner service module 5, that is, obtain the usage information of the target object for each product to be recommended. Then, the usage information forwarding unit 16 may send the recommendation result to the usage information forwarding unit 16, and the usage information forwarding unit 16 sends the recommendation result to the relationship optimization triggering unit 46 through the recommendation result receiving unit 45, so that the relationship optimization triggering unit 46 adjusts the association degree between the service category of the to-be-handled service and the to-be-recommended product based on the usage information.

For example, if the target object handles the tax payment service on the target service platform, there is a corresponding latest tax payment deadline, which may be N days apart from the time when the target object handles the tax payment service currently, at this time, the time when the target object actually completes the tax payment is the time when the target object handles the tax payment service, and the time may be later than the time when the target object exits the target service platform.

Alternatively, the target financial platform may determine whether the target object purchases the related product to be recommended based on the operation of the target object on the target business platform. Optionally, the target financial platform may recommend the product to be recommended to the target object by means of short message, telephone, and the like, and monitor information provided by the target object to the target financial platform in real time to determine whether the target object purchases the related product to be recommended.

Further, in the process that the relationship optimization triggering unit 46 adjusts the degree of association between the service category of the to-be-handled service and the to-be-recommended product based on the usage information, the relationship optimization triggering unit 46 may increase the degree of association between the product purchased by the target object and the service category of the to-be-handled service, and decrease the degree of association between the product not purchased by the target object and the service category of the to-be-handled service. Optionally, the relationship optimization triggering unit 46 may also improve the degree of association between part of products held by the target object and the service category of the service to be handled, and reduce the degree of association between part of products not held by the target object and the service category of the service to be handled. The determination of the aforementioned partial products may depend on rules predefined by the relevant staff.

It should be noted that, by adjusting and determining the association degree between the service category of the service to be handled and the product to be recommended according to the use information of the target object for each product to be recommended, it is convenient to more accurately determine the product actually required by the user when recommending the product to the user next time, so as to improve the success rate of recommending the product.

In an optional embodiment, in the process of adjusting the degree of association between the service category of the to-be-handled service and the to-be-recommended product based on the usage information, if the target object purchases the current to-be-recommended product, the target financial platform may update the target degree of association from the first degree of association to a second degree of association, and if the target object does not purchase the current to-be-recommended product, the target financial platform may update the target degree of association from the first degree of association to a third degree of association, where the target degree of association represents the degree of association between the service category of the to-be-handled service and the current to-be-recommended product, the second degree of association is higher than the first degree of association, and the first degree of association is higher than the third degree of association.

Optionally, in this embodiment, as shown in fig. 5, the maintenance module 3 further includes a relationship optimization unit 37. The relationship optimization triggering unit 46 may increase the association degree between all the products successfully recommended and the service categories of the services to be handled through the relationship optimization unit 37, and decrease the association degree between all the products failed in recommendation and the service categories of the services to be handled. The relation optimization unit 37 is used for optimizing the association degree between the product and the business category. When the target object purchases a certain product to be recommended, the product recommendation is successful, otherwise, when the target object does not purchase the certain product to be recommended, the product recommendation is failed.

It should be noted that by improving the association degree between the product successfully recommended and the service category of the service to be handled, the association degree between the product failed in recommendation and the service category of the service to be handled is reduced, and the effective adjustment of the association degree between the product and the service category is realized, so that the product can be conveniently and accurately recommended to the target object subsequently.

In an optional embodiment, after the at least one product to be recommended is displayed on the target business platform, the target financial platform may respond to a selection operation of the target object on the target business platform for the at least one product to be recommended, display a target purchase interface provided by the target financial platform through the target business platform, then detect whether the target object triggers a purchase operation on the target purchase interface, and record purchase information of the target object if the purchase operation on the target purchase interface triggered by the target object is detected. And the target purchasing interface is an interface corresponding to the product to be recommended selected by the target object.

Optionally, the service output unit 14 in the target financial platform may obtain, through the target service platform, a selection operation of the target object on the target service platform for at least one product to be recommended, then, in response to the selection operation, display a target purchase interface corresponding to the product to be recommended selected by the target object in the target service platform, and detect whether the target object purchases the selected product to be recommended, and if it is detected that the target object purchases the product to be recommended, the usage information receiving unit 15 may record purchase information of the target object, so as to implement the determination of the aforementioned usage information.

It should be noted that, by detecting the purchasing operation of the target object, the determination of the usage information of each product to be recommended by the target object is facilitated.

Optionally, an alternative embodiment in practical application after determining the product to be recommended is described. As shown in fig. 7, the recommending module 4 may query, through the maintaining module 3, at least one product to be recommended for the target object, and then the recommending module 4 may send a related name sheet of the product to be recommended to the service and product fusing module 1 to initiate recommendation, and then the service and product fusing module 1 outputs the product to be recommended to the partner service module 5 in an API manner. Then, the service and product fusion module 1 may obtain the usage information of the product to be recommended by the user through the partner service module 5, and return the usage information to the recommendation module 4, and the recommendation module 4 may register the usage information and feed back the usage information to the maintenance module 3 (i.e., data reflow in fig. 7), so as to optimize the association degree between the product and the service category through the maintenance module 3.

Optionally, in an optional embodiment, a target model may be set in the maintenance module 3, and the target model replaces the relationship query unit 35 to determine the corresponding product to be recommended according to the service information, and the target model may perform self-learning through backflow data including the usage information, so as to implement real-time updating and redeployment of the model itself. If the recommended effect is not as good as that of the model before updating in the deployment process, a rollback mode can be started to roll back to the model of the previous version. Optionally, the backflow data may further include service information corresponding to the usage information, and the backflow data is subjected to data precipitation, processing and combination to continuously perform model training and iteration, so that the target model may be quickly adapted to a new service category, and is upgraded and optimized during continuous usage of the user, thereby improving recommendation accuracy.

It should be noted that, based on the scheme provided by the application, recommendation channels for products are enriched, applicability to various service categories is ensured, in addition, by obtaining customers and recommending when users actively handle services, recommendation cost of advertisement type recommendation can be greatly reduced, recommendation accuracy is improved, services for providing and displaying and purchasing products to be recommended are output in an API mode and are integrated into a target service platform, usability and service experience of purchasing products by customers are improved, rejection of recommended events by customers is avoided, and recommendation success rate can be improved.

Therefore, the proposal provided by the application achieves the aim of recommending products for the target object according to the service requirements of the target object when the target object transacts services, thereby realizing the technical effect of improving the accuracy of recommending the products to the target object and further solving the technical problem of low accuracy of recommending financial products to users without difference in the prior art.

Example 2

According to an embodiment of the present invention, an embodiment of a product recommendation device is provided, wherein fig. 8 is a schematic diagram of an alternative product recommendation device according to an embodiment of the present invention, as shown in fig. 8, the device includes:

an obtaining module 801, configured to obtain service information generated when a target object transacts a service to be handled on a target service platform, where the target object is an object for which object information is registered at least on a target financial platform;

a first determining module 802, configured to determine at least one product to be recommended from a plurality of products provided by a target financial platform based on the business information;

the display module 803 is configured to display at least one product to be recommended on a target service platform, where the target service platform is configured to recommend at least one product to be recommended to a target object.

It should be noted that the acquiring module 801, the first determining module 802, and the displaying module 803 correspond to steps S201 to S203 in the foregoing embodiment, and the three modules are the same as the examples and application scenarios realized by the corresponding steps, but are not limited to the disclosure in embodiment 1.

Optionally, the determining module further includes: the first determining submodule is used for determining the service type of the service to be handled based on the service information; and the second determining submodule is used for determining at least one product to be recommended from a plurality of products provided by the target financial platform according to the service category of the service to be handled.

Optionally, the second determining sub-module further includes: the first determining unit is used for determining at least one initial product to be recommended corresponding to the service category of the service to be handled from a plurality of products according to the service category of the service to be handled; and the second determining unit is used for determining at least one product to be recommended from at least one initial product to be recommended according to the association degree between the service category of the service to be handled and each initial product to be recommended.

Optionally, the second determining sub-module further includes: an acquisition unit configured to acquire object information of a target object stored in a target financial platform; and the third determining unit is used for determining at least one product to be recommended from a plurality of products provided by the target financial platform based on the service category of the service to be dealt with and the object information of the target object according to the preset corresponding relation between the service category and the product.

Optionally, the product recommending apparatus further includes: the second determination module is used for determining the use information of the target object for each product to be recommended, wherein the use information is used for representing whether the target object holds the current product to be recommended before the target object finishes transacting the business to be recommended; and the adjusting module is used for adjusting the association degree between the service category of the service to be handled and the product to be recommended based on the use information.

Optionally, the adjusting module further includes: the first updating module is used for updating the target association degree from the first association degree to a second association degree if the target object purchases the current product to be recommended, wherein the target association degree represents the association degree between the service category of the service to be dealt with and the current product to be recommended, and the second association degree is higher than the first association degree; and the second updating module is used for updating the target association degree from the first association degree to a third association degree if the target object does not purchase the current product to be recommended, wherein the first association degree is higher than the third association degree.

Optionally, the product recommending apparatus further includes: the system comprises a corresponding module, a target financial platform and a target service platform, wherein the corresponding module is used for responding to the selection operation of a target object on the target service platform on at least one product to be recommended and displaying a target purchasing interface provided by the target financial platform through the target service platform, and the target purchasing interface is an interface corresponding to the product to be recommended selected by the target object; the detection module is used for detecting whether the target object triggers the purchase operation on the target purchase interface; and the recording module is used for recording the purchase information of the target object if the purchase operation triggered by the target object on the target purchase interface is detected.

Example 3

According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to execute the above-mentioned product recommendation method when being run.

Example 4

According to another aspect of the embodiments of the present invention, there is also provided an electronic device, where fig. 9 is a schematic diagram of an alternative electronic device according to the embodiments of the present invention, and as shown in fig. 9, the electronic device includes one or more processors; a memory for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement a method for executing a program, wherein the program is arranged to perform the above-mentioned product recommendation method when executed.

The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.

In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described apparatus embodiments are merely illustrative, and for example, a division of a unit may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or may not be executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.

The foregoing is only a preferred embodiment of the present invention, and it should be noted that it is obvious to those skilled in the art that various modifications and improvements can be made without departing from the principle of the present invention, and these modifications and improvements should also be considered as the protection scope of the present invention.

Claims (10)

1. A product recommendation method is applied to a target financial platform and comprises the following steps:

acquiring service information generated when a target object transacts a service to be handled on a target service platform, wherein the target object is an object of which at least object information is registered on the target financial platform;

determining at least one product to be recommended from a plurality of products provided by the target financial platform based on the business information;

and displaying at least one product to be recommended on the target service platform, wherein the target service platform is used for recommending the at least one product to be recommended to the target object.

2. The method of claim 1, wherein determining at least one product to be recommended from a plurality of products offered by the target financial platform based on the business information comprises:

determining the service type of the service to be handled based on the service information;

and determining at least one product to be recommended from a plurality of products provided by the target financial platform according to the service category of the service to be dealt with.

3. The method of claim 2, wherein determining at least one product to be recommended from a plurality of products provided by the target financial platform according to the service category of the service to be handled comprises:

determining at least one initial product to be recommended corresponding to the service category of the service to be handled from the plurality of products according to the service category of the service to be handled;

and determining the at least one product to be recommended from the at least one initial product to be recommended according to the degree of association between the service category of the service to be handled and each initial product to be recommended.

4. The method of claim 2, wherein determining at least one product to be recommended from a plurality of products provided by the target financial platform according to the business category of the business to be dealt with comprises:

acquiring object information of the target object stored in the target financial platform;

and determining at least one product to be recommended from a plurality of products provided by the target financial platform based on the service category of the service to be dealt with and the object information of the target object according to a preset corresponding relation between the service category and the products.

5. The method of claim 3, wherein after displaying at least one product to be recommended on the target business platform, the method further comprises:

determining the use information of the target object for each product to be recommended, wherein the use information is used for representing whether the target object holds the current product to be recommended before the business to be handled is handled;

and adjusting the association degree between the service category of the to-be-handled service and the to-be-recommended product based on the use information.

6. The method of claim 5, wherein adjusting the degree of association between the service category of the to-do service and the to-be-recommended product based on the usage information comprises:

if the target object purchases the current product to be recommended, updating the target association degree from a first association degree to a second association degree, wherein the target association degree represents the association degree between the service category of the service to be handled and the current product to be recommended, and the second association degree is higher than the first association degree;

and if the target object does not purchase the current product to be recommended, updating the target association degree from the first association degree to a third association degree, wherein the first association degree is higher than the third association degree.

7. The method according to claim 1 or 3, wherein after displaying at least one product to be recommended on the target business platform, the method further comprises:

responding to the selection operation of the target object on the target business platform for the at least one product to be recommended, and displaying a target purchasing interface provided by the target financial platform through the target business platform, wherein the target purchasing interface is an interface corresponding to the product to be recommended selected by the target object;

detecting whether the target object triggers a purchase operation on the target purchase interface;

and if the purchase operation triggered by the target object on the target purchase interface is detected, recording the purchase information of the target object.

8. A product recommendation device, comprising:

the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring service information generated when a target object transacts a service to be handled on a target service platform, and the target object is an object of which at least object information is registered on a target financial platform;

a first determination module, configured to determine at least one product to be recommended from a plurality of products provided by the target financial platform based on the business information;

and the display module is used for displaying at least one product to be recommended on the target service platform, wherein the target service platform is used for recommending the at least one product to be recommended to the target object.

9. A computer-readable storage medium, in which a computer program is stored, wherein the computer program is arranged to execute the product recommendation method of any one of claims 1 to 7 when running.

10. An electronic device, characterized in that the electronic device comprises one or more processors; memory for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement a method for running a program, wherein the program is arranged to perform the product recommendation method of any of claims 1 to 7 when run.

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