WO2021169659A1

WO2021169659A1 - Resource information pushing method and device, server, and storage medium

Info

Publication number: WO2021169659A1
Application number: PCT/CN2021/072131
Authority: WO
Inventors: 王天齐; 郑景飞; 伍平平; 马明浩; 唐逸立
Original assignee: 中国银联股份有限公司
Priority date: 2020-02-24
Filing date: 2021-01-15
Publication date: 2021-09-02
Also published as: CN111371853A; TWI803823B; TW202133080A; CN111371853B

Abstract

The present application relates to the field of data processing, and provides a resource information pushing method and device, a server, and a storage medium. The method comprises: acquiring resource consumption information and resource provider information of users; determining priority levels of the users on the basis of the resource consumption information and the resource provider information, and determining priority levels of resource information associated with the users; treating a user having a priority level higher than a first preset standard priority level as a target user, and treating the resource information associated with the user and having a priority level higher than a second preset standard priority level as target resource information; and pushing, to the target user, the target resource information associated with the target user. The technical solution of the present application allows resource information to be pushed to users in a more accurate manner.

Description

Resource information pushing method, device, server and storage medium

Cross-references to related applications

This application claims the priority of the Chinese patent application 202010113562.2 entitled "Resource Information Push Method, Device, Server and Storage Medium" filed on February 24, 2020, and the entire content of this application is incorporated herein by reference.

Technical field

This application belongs to the field of data processing, and in particular relates to a method, device, server, and storage medium for pushing resource information.

Background technique

In recent years, with the development of electronic information technology, electronic information technology has been applied in more and more fields, such as transaction fields, payment fields, and so on.

In order to facilitate users to conduct transactions, various resources can be pushed to users. Currently, the server uniformly recommends resources to a large number of users. However, there are differences between users, and the method of uniformly recommending resources is less accurate for users.

Summary of the invention

The embodiments of the present application provide a method, a device, a server, and a storage medium for pushing resource information, which can improve the accuracy of pushing resource information to users.

In the first aspect, an embodiment of the present application provides a method for pushing resource information, including:

Obtain user resource consumption information and resource provider information;

Based on resource consumption information and resource provider information, determine the priority of the user, and determine the priority of the resource information associated with the user;

Taking a user whose priority is higher than the first preset standard priority as the target user, and taking the resource information associated with the user whose priority is higher than the second preset standard priority as the target resource information;

Push the target resource information associated with the target user to the target user.

In the second aspect, an embodiment of the present application provides a resource information pushing device, including:

The information acquisition module is used to acquire the user's resource consumption information and resource provider information;

The priority determination module is used to determine the priority of the user and the priority of the resource information associated with the user based on the resource consumption information and the resource provider information;

The target determination module is configured to use a user with a priority higher than the first preset standard priority as the target user, and use resource information associated with the user with a priority higher than the second preset standard priority as the target resource information;

The push module is used to push target resource information associated with the target user to the target user.

In the third aspect, the embodiments of the present application provide a server, including a processor, a memory, and a computer program stored on the memory and capable of running on the processor. The computer program is executed by the processor to implement the technical solutions in the first aspect Resource information push method.

In the fourth aspect, the embodiments of the application provide a computer-readable storage medium, the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to realize the resource information in the technical solution of the first aspect Push method.

The embodiments of the present application provide a method, device, server, and storage medium for pushing resource information. Based on resource consumption information and resource provider information, the priority of a user is determined, and the priority of resource information associated with the user is determined. Push resource information associated with the user whose priority is higher than the second preset standard priority to a user whose priority is higher than the first preset standard priority. The information of the resource provider represents the relevant information of the resource provider and can make up for the missing part of the resource consumption information. Combining resource consumption information and resource provider information, and using priority, the accurate push of resource information to users is realized, and the accuracy of pushing resource information to users is improved.

Description of the drawings

The present application can be better understood from the following description of the specific implementation manners of the present application in conjunction with the accompanying drawings. Wherein, the same or similar reference signs indicate the same or similar features.

FIG. 1 is a flowchart of an embodiment of a method for pushing resource information provided by this application;

2 is a flowchart of another embodiment of the resource information pushing method provided by this application;

FIG. 3 is a schematic structural diagram of an embodiment of a resource information pushing device provided by this application;

4 is a schematic structural diagram of another embodiment of the resource information pushing device provided by this application;

FIG. 5 is a schematic structural diagram of another embodiment of the resource information pushing device provided by this application;

FIG. 6 is a schematic structural diagram of still another embodiment of the resource information pushing device provided by this application;

FIG. 7 is a schematic structural diagram of an embodiment of a server provided by this application.

Detailed ways

The features and exemplary embodiments of various aspects of the present application will be described in detail below. In the following detailed description, many specific details are proposed in order to provide a comprehensive understanding of the application. However, it is obvious to those skilled in the art that this application can be implemented without some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by showing examples of the present application. This application is by no means limited to any specific configurations and algorithms proposed below, but covers any modification, replacement and improvement of elements, components and algorithms without departing from the spirit of this application. In the drawings and the following description, well-known structures and technologies are not shown in order to avoid unnecessary obscurity of the application.

This application provides a method, a device, a server, and a storage medium for pushing resource information, which can be applied to a scenario of pushing resource information to a user. For example, the scenarios of pushing services to users, pushing products to users, or pushing activities to users are not limited here. The method for pushing resource information can be executed by a service device such as a server. The number of servers is not limited here, and the number of servers can be set according to the number of users and other factors. For example, the method for pushing resource information can be executed by a server cluster. In the embodiments of this application, the cross-comparison of resource consumption information and resource provider information can be used according to the comprehensive use of the user’s resource consumption information and resource provider information, and the priority of the user and the priority of the resource information may be determined according to the user’s priority. Users push resource information to improve the accuracy of resource information push.

Fig. 1 is a flowchart of an embodiment of a method for pushing resource information provided by this application. As shown in FIG. 1, the method for pushing resource information may include step S101 to step S104.

In step S101, the user's resource consumption information and resource provider information are acquired.

The user's resource consumption information is related to the user, and can characterize the user's own information, and also characterize the user's orientation of resource consumption, such as the user's preference for resource consumption. Corresponding to the user's resource consumption information, a user resource consumption database can be established, and the user's resource consumption information can be stored in the user resource consumption database. In some examples, the user resource consumption database can be set in a single big data host cluster configured with 24C or 256G or 40T, which is not limited here.

In some examples, resource consumption information includes, but is not limited to, one or more of the following: user information, user resource consumption time preference information, user resource consumption preference information, user resource consumption type preference information, user consumption resource The type preference information of the resource provider, the location information of the resource provider where the user consumes resources, and the relevance information of the resource provider where the user consumes resources. Wherein, the resource provider association information of the resource consumed by the user is used to characterize the association of two or more resource providers from the source of the user's consumption of resources, for example, characterize the similarity of two or more resource providers from the source of the user's consumption of resources.

In the transaction scenario, the resource provider may specifically be a merchant. The resource consumption information can be obtained from the historical information of the transaction of the user account. For example, resource consumption information may include user account number, balance in user account, user transaction time preference, user preference for transaction selection, user selection transaction type preference, user selection transaction type preference, user selection transaction merchant location, user The selection of one or more items of information such as the similarity of the merchants for the transaction is not limited here.

For example, in a transaction scenario, the storage form of resource consumption information can be as shown in Table 1 below.

Table I

The resource provider information is related to the resource provider of the resource consumed by the user, and can characterize the relevant information of the resource provider. Corresponding to the user's resource provider information, a resource provider database can be established, and the resource provider information can be stored in the resource provider database. In some examples, the resource provider database can be set in a single Kafka cluster configured with 24C/256G/40T, which is not limited here.

In some examples, the resource provider information includes one or more of the following: resource provider name information, resource provider location information, resource provider location information, resource provider type information, resource provider evaluation information, Information on the popularity of the resource provider and the relevance information provided by the resource provider’s resources. Among them, the resource provision relevance information of the resource provider is used to characterize the relevance of resources provided by two or more resource providers, for example, characterize the similarity of resources provided by two or more resource providers.

In the transaction scenario, the resource provider may specifically be a merchant. The resource provider information can be read through a third-party interface, data file import, or manual input collection to obtain public or shared merchant transaction information data. For example, the resource provider information may include one or more of information such as the name of the business, the location of the business, the location of the business district, the type of the business, the evaluation of the business, the popularity of the business, and the similarity of the business consumption, which is not limited here.

For example, in a transaction scenario, the storage form of resource provider information can be as shown in Table 2 below.

Table II

In order to standardize the resource provider information and improve the accuracy of the standardized resource provider information, data cleaning and standardization processing can be performed on the acquired resource provider information for use in subsequent processes. In the process of data cleaning and standardization, the rules formed in the standardization process, such as user location extraction rules, and dictionaries such as business name address proper nouns, stop words, etc., are imported into the rule library or thesaurus. The rule database and thesaurus can be used in the process of data cleaning and standardization of new information.

In step S102, based on the resource consumption information and the resource provider information, the priority of the user is determined, and the priority of the resource information associated with the user is determined.

Combining the user’s resource consumption information and resource provider information, algorithms or strategies can be used to determine whether the user’s resource consumption is active, and the user’s resource consumption potential can also be determined, so as to estimate the user’s demand for resources, and then determine the user’s resource consumption. Priority and the priority of the resource associated with the user. The algorithm or strategy is not limited here. For example, a gradient boosting decision tree (Gradient Boosting Decision Tree, GBDT) algorithm, an association rule algorithm that is Apriori algorithm, a collaborative filtering algorithm, etc. can be used.

The specific expression of the priority is not limited here. For example, the priority may include the first level to the Nth level, where the priority of the i-1th level is higher than the priority of the ith level, 1<i≤N , I and N are positive integers. For another example, the priority may include a high-level, a medium-level, and a low-level, where the high-level priority is higher than the medium-level priority, and the medium-level priority is higher than the low-level priority.

The server can determine which users to prefer to push resource information according to the user's priority. A user can be associated with multiple resource information, and the resource information associated with different users can be different. The server can also determine which resource information to preferentially push to the user according to the priority of the resource information.

In some examples, the resource information may include, but is not limited to, one or more of resource providers, resource types, and resource provision schemes. For example, in a transaction scenario, the resource provider may be a merchant, the resource category may be a commodity category, and the resource provision plan may be a commodity sales plan such as a preferential plan.

In step S103, the user whose priority is higher than the first preset standard priority is taken as the target user, and the resource information associated with the user whose priority is higher than the second preset standard priority is taken as the target resource information.

Among them, the first preset standard priority can be set according to the work scenario and work requirements, which is not limited here, and the first preset standard priority can be changed according to specific conditions. The second preset standard priority can be set according to the work scenario and work requirements, which is not limited here, and the second preset standard priority can be changed according to specific conditions. The first preset standard priority and the second preset standard priority may be independent of each other.

The target user is the user who is given priority to push resource information. The target resource information associated with the user is the resource information that is preferentially pushed to the user. The priority of the same resource information associated with different users can be different, so that the target resource information pushed to different users can be different, which can be specifically determined according to the priority of the resource information associated with each user.

In step S104, the target resource information associated with the target user is pushed to the target user.

Among them, the server can push the target resource information associated with the target user to the target user through the application program, namely APP, etc. For example, the real-time data stream is used to push the target resource information associated with the target user to the target user, and the real-time data stream may specifically be a Kafka real-time data stream. The server can also push the target resource information associated with the target user to the target user through short messages and other methods. The method of pushing target resource information associated with the target user to the target user is not limited here.

In the embodiment of the present application, based on the resource consumption information and the resource provider information, the priority of the user is determined, and the priority of the resource information associated with the user is determined. Push resource information associated with the user whose priority is higher than the second preset standard priority to a user whose priority is higher than the first preset standard priority. The information of the resource provider represents the relevant information of the resource provider and can make up for the missing part of the resource consumption information. Combining resource consumption information and resource provider information, and using priority, the accurate push of resource information to users is realized, and the accuracy of pushing resource information to users is improved.

In some examples, the above step S102 may be implemented through user activity information and resource consumption potential information. Specifically, based on the resource consumption information and resource provider information, the user's activity information and resource consumption potential information are set. According to the user's activity information and resource consumption potential information, the priority of the user is determined, and the priority of the resource information associated with the user is determined.

The user's activity information is used to characterize the user's activity, and may indicate the number of times the user has consumed resources, the amount of user resource consumption, etc., which are not limited here. For example, in a transaction scenario, the user's activity information indicates that the user's activity is higher, which means that the user's transaction volume is greater, and the transaction volume may refer to the number of transactions, transaction costs, and so on. The activity information of the user may be specifically implemented as an activity score or an activity rating, etc., which is not limited here. For example, in a transaction scenario, the user's activity information may be reflected in the user's bank card activity. The activity of a bank card may include active, inactive, recession, arousal, sleep and so on. Correspondingly, bank cards can be divided into active cards, inactive cards, declining cards, wake-up cards, sleep cards, etc. according to their activity.

The user's resource consumption potential information is used to characterize the user's resource consumption potential, and can indicate the user's total resource consumption potential, the user's potential to consume a certain type of resource, and so on, which is not limited here. For example, in a transaction scenario, the user's resource consumption potential information indicates that the user's resource consumption potential is higher, indicating that the greater the amount of resources that the user can consume is predicted. The amount of resources may refer to the total amount of resources, the amount of certain types of resources, and so on. The user's resource consumption potential information can be specifically realized as a resource consumption potential score or a resource consumption potential classification, etc., which is not certain here. For example, in a transaction scenario, the user's resource consumption potential can include high-level, medium-level, low-level, and so on.

For example, in a transaction scenario, combining the user’s resource consumption information and resource provider information, through the user’s transaction information such as the number of transactions and transaction amount in the resource consumption information and resource provider information, it can be determined whether the user’s bank card is active or not. Decline, whether to sleep, that is, determine the user's activity. The GBDT algorithm can also be used to determine the user's resource consumption potential through the use of resource consumption information and the user's historical information in the resource provider information, such as the use of e-commerce applications, the history of the business circle where the user is trading, and so on. According to the user's activity information and resource consumption potential information, the priority of the pushed user and the priority of the pushed resource information are determined.

For another example, in a transaction scenario, combining the user's resource consumption information and resource provider information, the user's industry preferences, merchant consumption history and other resource consumption information, as well as the user's e-commerce application preferences, merchant attention history and other resources are provided Party information, using the Apriori algorithm to determine the merchant in the resource information pushed to the user.

In some examples, the resource information includes resource providers. A set of candidate resource providers can be generated according to the category of each resource provider. The pruning algorithm is used to process the candidate set of resource providers, and the resource providers who provide users with high-frequency resources for consumption are selected as the resource providers in the resource information. The above process can be repeated to obtain multiple resource providers in the resource information.

In the embodiments of this application, due to the participation of resource provider information, for users with low activity levels, such as users whose transaction cards are evaluated as sleeping cards, a certain amount of resource consumption of the user can also be obtained through resource provider information mining. Ability to push appropriate resource information for the user.

In some examples, the target decision model may be used to obtain the priority of the user and/or the priority of the resource information associated with the user. Specifically, for each user, the user's resource consumption information and resource provider information are used as the input of each target decision model, and the output result of each target decision model is obtained. The output result represents the priority of the user and/or the priority of the resource information associated with the user under the target requirement corresponding to the target decision model. Calculate the sum of the product of the output result of each target decision model and the weight of the target decision model. The priority of the user and/or the priority of the resource information associated with the user is determined according to the sum of the products.

The target decision model may specifically be a classifier. The number of target decision models can be multiple. If multiple target decision models are selected, different target decision models correspond to different target requirements. In this embodiment, the comprehensive priority of the user and/or the priority of the resource information associated with the user can be obtained according to multiple different target requirements.

The following is an example for description. The following formula (1) can be used to obtain the priority of the integrated user and/or the priority of the resource information associated with the user.

Among them, x is the input user’s resource consumption information and resource provider information. Specifically, the user’s resource consumption information and resource provider information can be expressed as a vector; F(x) is the user’s integrated priority and/or the user’s The priority of the associated resource information, specifically, can be divided into three priority levels: medium, high, and low; h _m (x) is the output result of the m-th target decision model; γ _m is the weight of the target decision model.

Further, the resource consumption result information fed back after the target user receives the target resource information can also be collected. Use the resource consumption result information to update the target decision model to improve the accuracy of the output result of the target decision model.

The priority of the user determined by the server and the priority of the resource information associated with the user are both predicted by the server. In order to further improve the accuracy of server prediction, the target decision model can be continuously updated. After the target user receives the target resource information, the target user may consume resources corresponding to the target resource information, or may not consume resources corresponding to the target resource information. The resource consumption result information fed back may characterize the actual resource consumption of the target user after receiving the target resource information, and may include the priority of the actual user and/or the priority of the actual resource information associated with the user. The target decision model will continuously fit the priority of the actual user and/or the priority of the actual target resource information associated with the user, and the priority of the user predicted by the target decision model and/or the target resource information associated with the user. The residual of the priority makes the output result of the target decision model approach the priority of the actual user and/or the priority of the actual target resource information associated with the user.

For example, the target decision model can be updated by the following formula (2).

F _m (x)=F _m-1 (x)+γ _m h _m (x) (2)

Among them, F _m-1 (x) is the weighted calculation sum of the output results of the previous m-1 target decision model. F _m (x) is the weighted calculation sum of the output results of the previous m target decision model.

_{It is also possible to optimize the target decision model by updating h m} (x) in the above equations (1) and (2) to reduce the error between the output result of the target decision model and the actual result. _{For example, the optimization of h m} (x) can be achieved by the following equation (3).

Among them, y _i is the i-th actual result, that is, the priority of the i-th user and/or the priority of the resource information associated with the i-th user. L(y _i , F _m-1 (x _i )+h(x _i )) is the relational expression _{of y i} and F _m-1 (x _i )+h(x _{i ).}

Fig. 2 is a flowchart of another embodiment of a method for pushing resource information provided by this application. The difference between FIG. 2 and FIG. 1 is that the resource information pushing method shown in FIG. 2 may further include step S105, and step S102 shown in FIG. 1 can be refined into step S1021 shown in FIG. 2.

In step S105, the credibility calculation model is used to calculate the credibility of the resource consumption information and the credibility of the resource provider information.

In order to further improve the accuracy of pushing resource information, it is possible to use highly reliable priority resource consumption information and resource provider information to participate in the step of determining the priority of the user and the priority of the resource information associated with the user. Specifically, the algorithm used in the credibility calculation model may include a random forest algorithm, or other algorithms may be used, which is not limited here. The credibility of resource consumption information represents the degree to which the resource consumption information can be trusted. The credibility of the resource provider's information represents the degree to which the resource provider's information can be trusted. In some examples, credibility is expressed in numerical terms. For example, a credibility of information of 80 to 100 indicates that the information is accurate; a credibility of information of 60 to 80 indicates that the information is credible and available; a credibility of information of 40 to 60 indicates that the information is partially available; the credibility of information is 0 to 40 indicate that the information needs to be improved.

This application can use the integrated learning method to calculate and classify the credibility. Integrated learning solves a single prediction problem by building a combination of several models. The following uses the random forest algorithm as an example to describe the credibility calculation, but it should be noted that in the embodiment of the present application, other algorithms may also be used to perform the credibility calculation. The random forest algorithm is a sub-category of ensemble learning, which relies on the voting selection of the decision tree to determine the final classification result. Specifically, the following formula (4) can be used to calculate the information entropy. In the forest stochastic algorithm, a decision tree is used to classify the reliability. Information entropy is the foundation of decision trees, which can be used to determine the basis of resource consumption information and the selection order of resource provider information during the process of credibility classification of decision trees.

I(X=xi)=-log ₂ p(x _i ) (4)

Among them, I(x) represents the information of random variables; p( _xi ) refers to the probability when _xi _{occurs; and xi} is the resource consumption information and resource provider information of the i-th user.

A decision tree is a tree structure in which each internal node represents a test on an attribute, each branch represents a test output, and each leaf node represents a category. In this example, each branch represents an output of credibility calculation, and each leaf node represents a credibility category.

In some examples, multiple credibility calculation models may be used to perform multi-dimensional calculations on the credibility of resource consumption information and the credibility of resource provider information. For example, the credibility can be assessed from both the source of the information and the information itself. Specifically, the credibility of the information source can be evaluated from the aspects of the person who entered the information, whether the entry has a verification link, whether it has undergone technical processing and manual data cleaning, etc. Here, the credibility of the user behavior preference information in the resource consumption information and the resource provider information is taken as an example to illustrate the credibility evaluation of the information itself. The credibility of user behavior preference information can be obtained through comprehensive evaluation of the credibility of the user's resource consumption, the credibility of the user's resource consumption method, the credibility of the user's resource consumption habits, the credibility of the user's resource consumption type information, and the weight. Spend. The credibility of the information source, the credibility of the information itself, the weight of the credibility of the information source and the weight of the credibility of the information itself can be used to comprehensively obtain the credibility of the user's resource consumption information and the information of the resource provider Credibility.

The steps of credibility calculation and classification can be performed by a single host in a big data host cluster configured as 24C/256G/40T, which is not limited here.

In step S1021, based on the resource consumption information and the resource provider information, according to the credibility of the resource consumption information and the credibility of the resource provider information, the priority of the user is determined, and the priority of the resource information associated with the user is determined .

Among them, combining the credibility of the resource consumption information and the credibility of the resource provider information, the resource consumption information and the resource provider information for determining the priority of the user and the priority of the resource information associated with the user can be selected. For example, selecting highly reliable resource consumption information and resource provider information to determine the priority of the user and the priority of the resource information associated with the user, so as to further improve the accuracy and reliability of pushing resource information.

In the embodiment of the present application, the server may correspondingly push resource information to the user according to the user's resource consumption mode. Wherein, the priority of the resource information includes, but is not limited to, the resource information including one or more of the priority of the resource provider, the priority of the resource category, and the priority of the resource provision plan.

In some embodiments, the mode in which the user consumes resources is an online mode. For example, in a transaction scenario, the server may obtain the user's location from the user's application. The server matches the information of the resource provider according to the user's transaction merchant preference and transaction merchant type preference in the resource consumption information to obtain the merchant name, merchant type, merchant popularity and other information of the merchant in the area where the user is located. And according to the matching, obtain the business name, business type, business popularity and other information of the business in the area where the user location is located, and evaluate the resource consumption potential of the user in the area where the user location is located. Combining the resource consumption potential and user activity in the area, determine resource information with a priority higher than the second preset standard priority. The resource information with priority higher than the second preset standard priority can be pushed to users through Kafka real-time data stream. For example, push resource information to the user in the user's application.

In some examples, the relevance of users represented by resource consumption information and resource provider information and the relevance of resource providers can be used to cluster users, so that users in the same cluster obtained by clustering can be resourced. Push of information.

Specifically, the users are clustered to obtain at least two clusters. For each cluster, select a user's resource consumption information and resource provider information as the cluster center of the cluster. Calculate the resource consumption information of other users in the cluster except the user corresponding to the cluster center and the distance between the resource provider information and the cluster center. According to the distance, update the cluster and the cluster center of the cluster until the updated cluster center is the same as the cluster center before the update.

The initial clustering of users can be randomly clustered or clustered according to a preset rule, which is not limited here. The resource consumption information and resource provider information of each user can be represented in the form of vectors. The cluster center of a cluster should be the resource consumption information and resource provider information of the user who is closest to the resource consumption information and resource provider information of other users in the cluster. Therefore, by calculating the distance between the resource consumption information and resource provider information of other users in the cluster except the user corresponding to the cluster center and the cluster center, and based on the distance, the division of the cluster and the cluster center are updated to ensure the clustering. accuracy. The updated cluster center is the same as the cluster center before the update, which means that the cluster center is stable and the current clustering result can be maintained.

For example, the cross-validation method can be used to select the number of clusters k. Use the following formula (5) to calculate the Euclidean distance between the resource consumption information and resource provider information of each user in the cluster and the cluster center, so as to update the cluster division and cluster center based on the Euclidean distance.

Among them, dist _ed (x ⁽ⁱ⁾ , x ^(j) ) is the vector formed by the resource consumption information and resource provider information of the i-th user in the cluster and the resource consumption information and resource provider information of the j-th user The Euclidean distance of the vector; n is the total number of users in the cluster; u is the vector dimension.

The resource consumption of users in the same cluster has a certain similarity, and at least one item of resource information pushed to users in the same cluster is the same. For example, in a transaction scenario, the resource categories in the resource information pushed to users in the same cluster are all "catering", but the transaction discount algorithm involved in the resource provision scheme in the resource information pushed to users in the same cluster different.

The user's resource consumption mode is the online mode. The server corresponding to the online mode may include a single big data host cluster configured as 24C/256G/40T and a single Kafka cluster configured as 24C/256G/40T, which is not limited here.

In other embodiments, the mode in which the user consumes resources is an offline mode. For example, in a transaction scenario, a user uses a bank card to conduct a transaction, uses the transaction flow in the resource consumption information to determine the user’s business district, and uses a collaborative filtering algorithm to match the business district’s location in the resource provider’s information To determine the target resource information to be pushed, combined with information such as the name of the merchant, the type of the merchant, and the similarity of the merchant’s consumption, combined with the user’s activity. For example, one or more of the priority of the resource provider, the priority of the resource category, and the priority of the resource provision plan in the target resource information can be determined, and the priority is higher than the second preset standard priority resource provider One or more of, resource category, and resource provision plan are pushed to the user as target resource information, that is, the target resource information pushed to the user is determined. In some examples, the target resource information can be pushed to the user through the Kafka real-time data stream.

The user's resource consumption mode is offline. The server corresponding to the offline mode may include a single big data host cluster configured as 24C/256G/40T and a single Kafka cluster configured as 24C/256G/40T, which is not limited here.

FIG. 3 is a schematic structural diagram of an embodiment of the resource information pushing device provided by this application. As shown in FIG. 3, the resource information pushing device 200 may include an information acquiring module 201, a priority determining module 202, a target determining module 203, and a pushing module 204.

The information acquisition module 201 is used to acquire user resource consumption information and resource provider information.

In some examples, the resource consumption information includes one or more of the following: user information, user resource consumption time preference information, user resource consumption resource provider preference information, user resource consumption type preference information, user resource consumption resource provision Party type preference information, location information of the resource provider where the user consumes resources, and information about the relevance of the resource provider where the user consumes resources.

In some examples, the resource provider information includes one or more of the following: resource provider name information, resource provider location information, resource provider location information, resource provider type information, resource provider evaluation information, Information on the popularity of the resource provider and the relevance information provided by the resource provider’s resources.

The priority determination module 202 is configured to determine the priority of the user based on the resource consumption information and the resource provider information, and determine the priority of the resource information associated with the user.

In some examples, the resource information includes one or more of resource providers, resource types, and resource provision schemes.

In some examples, the priority of the resource information includes one or more of the resource information including the priority of the resource provider, the priority of the resource category, and the priority of the resource providing solution.

The target determination module 203 is configured to use a user with a priority higher than a first preset standard priority as a target user, and use resource information associated with the user with a priority higher than a second preset standard priority as the target resource information.

The pushing module 204 is used to push target resource information associated with the target user to the target user.

In some examples, the pushing module 204 may be specifically configured to push the target resource information associated with the target user to the target user using real-time data streams.

In the embodiment of the present application, based on the resource consumption information and the resource provider information, the priority of the user is determined, and the priority of the resource information associated with the user is determined. Push resource information associated with the user whose priority is higher than the second preset standard priority to a user whose priority is higher than the first preset standard priority. The resource provider information represents the relevant information of the resource provider and can make up for the missing part of the resource consumption information. Combining resource consumption information and resource provider information, and using priority, the accurate push of resource information to users is realized, and the accuracy of pushing resource information to users is improved.

In some examples, the priority determination module 202 may be specifically configured to: set user activity information and resource consumption potential information based on resource consumption information and resource provider information; determine according to user activity information and resource consumption potential information The priority of the user, and the priority of determining the resource information associated with the user.

FIG. 4 is a schematic structural diagram of another embodiment of the resource information pushing device provided by this application. The difference between FIG. 4 and FIG. 3 is that the resource information pushing device 200 shown in FIG. 4 may further include a collection module 205 and an update module 206.

The priority determining module 202 in the foregoing embodiment can be specifically used to: for each user, take the user's resource consumption information and resource provider information as the input of each target decision model, and obtain the output result of each target decision model; Calculate the sum of the product of the output result of each target decision model and the weight of the target decision model; determine the priority of the user and/or the priority of the resource information associated with the user according to the sum of the products.

Among them, the output result represents the priority of the user and/or the priority of the resource information associated with the user under the target requirements corresponding to the target decision model

The collection module 205 is configured to collect resource consumption result information fed back by the target user after receiving the target resource information.

The update module 206 is used to update the target decision model using the resource consumption result information.

FIG. 5 is a schematic structural diagram of another embodiment of the resource information pushing device provided by this application. The difference between FIG. 5 and FIG. 3 is that the resource information pushing device 200 shown in FIG. 5 may further include a credibility calculation module 207.

The credibility calculation module 207 can be used to use the credibility calculation model to calculate the credibility of resource consumption information and the credibility of resource provider information.

The priority determining module 202 in the foregoing embodiment may be specifically used to determine the priority of the user based on the resource consumption information and the resource provider information, according to the credibility of the resource consumption information and the credibility of the resource provider information, and Determine the priority of the resource information associated with the user.

FIG. 6 is a schematic structural diagram of still another embodiment of the resource information pushing device provided by this application. The difference between FIG. 6 and FIG. 3 is that the resource information pushing device 200 shown in FIG. 6 may further include a clustering module 208.

The clustering module 208 can be used to: cluster users to obtain at least two clusters; for each cluster, select the resource consumption information and resource provider information of a user as the cluster center; The resource consumption information of users other than the user and the distance between the resource provider information and the cluster center; according to the distance, the cluster and the cluster center of the cluster are updated until the updated cluster center is the same as the cluster center before the update.

In some examples, the resource information includes one or more of a resource provider, a resource category, and a resource providing solution, and at least one of the resource information pushed to users in the same cluster is the same.

FIG. 7 is a schematic structural diagram of an embodiment of a server provided by this application. As shown in FIG. 7, the server 300 includes a memory 301, a processor 302, and a computer program stored on the memory 301 and running on the processor 302.

In an example, the aforementioned processor 302 may include a central processing unit (CPU), or a specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

The memory 301 may include a large-capacity memory for data or instructions. By way of example and not limitation, the memory 301 may include an HDD, a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the storage 301 may include removable or non-removable (or fixed) media. Under appropriate circumstances, the storage 301 can be opened inside or outside the server 300 in a terminal hotspot. In a particular embodiment, the memory 301 is a non-volatile solid state memory. In a particular embodiment, the memory 301 includes read-only memory (ROM). Where appropriate, the ROM can be mask-programmed ROM, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), electrically rewritable ROM (EAROM) or flash memory or A combination of two or more of these.

The processor 302 runs the computer program corresponding to the executable program code by reading the executable program code stored in the memory 301, so as to implement the resource information pushing method in the foregoing embodiment.

In an example, the server 300 may further include a communication interface 303 and a bus 304. Among them, as shown in FIG. 7, the memory 301, the processor 302, and the communication interface 303 are connected through the bus 304 and complete the communication with each other.

The communication interface 303 is mainly used to implement communication between various modules, devices, units and/or devices in the embodiments of the present application. The input device and/or output device can also be accessed through the communication interface 303.

The bus 304 includes hardware, software, or both, and couples the components of the server 300 to each other. For example and not limitation, the bus 304 may include an accelerated graphics port (AGP) or other graphics bus, an enhanced industry standard architecture (EISA) bus, a front side bus (FSB), a hypertransport (HT) interconnect, an industry standard architecture (ISA) ) Bus, unlimited bandwidth interconnect, low pin count (LPC) bus, memory bus, microchannel architecture (MCA) bus, peripheral component interconnect (PCI) bus, PCI-Express (PCI-X) bus, serial advanced Technical Attachment (SATA) bus, Video Electronics Standards Association Local (VLB) bus or other suitable bus or a combination of two or more of these. Where appropriate, the bus 304 may include one or more buses. Although the embodiments of this application describe and show a specific bus, this application considers any suitable bus or interconnection.

An embodiment of the present application also provides a computer-readable storage medium having a computer program stored on the computer-readable storage medium. When the computer program is executed by a processor, the method for pushing resource information in the above-mentioned embodiment can be implemented, and can achieve The same technical effect, in order to avoid repetition, will not be repeated here. Wherein, the computer-readable storage medium may include non-transitory computer-readable storage media, such as read-only memory (Read-Only Memory, ROM for short), Random Access Memory (RAM for short), and magnetic disks. Or CD etc.

It should be clear that the various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. Place. For the device embodiment, the server embodiment, and the computer-readable storage medium embodiment, see the description part of the method embodiment for relevant details. The application is not limited to the specific steps and structures described above and shown in the figures. Those skilled in the art can make various changes, modifications and additions, or change the order between steps after grasping the spirit of the application. And, for the sake of brevity, a detailed description of the known method and technology is omitted here.

The above describes various aspects of the present application with reference to the flowcharts and/or block diagrams of the methods, devices (systems) and machine program products according to the embodiments of the present application. It should be understood that each block in the flowchart and/or block diagram and the combination of each block in the flowchart and/or block diagram can be implemented by a program or instruction. These programs or instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to generate a machine so that these programs or instructions are executed by the processor of the computer or other programmable data processing device Enables the realization of functions/actions specified in one or more blocks of the flowchart and/or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a dedicated processor, a special application processor, or a field programmable logic circuit. It can also be understood that each block in the block diagram and/or flowchart and the combination of the blocks in the block diagram and/or flowchart can also be implemented by dedicated hardware that performs specified functions or actions, or can be implemented by dedicated hardware and A combination of computer instructions.

Those skilled in the art should understand that the above-mentioned embodiments are all exemplary rather than restrictive. Different technical features appearing in different embodiments can be combined to achieve beneficial effects. Those skilled in the art should be able to understand and implement other modified embodiments of the disclosed embodiments on the basis of studying the drawings, the description, and the claims. In the claims, the term "comprising" does not exclude other means or steps; the quantifier "a" does not exclude multiple; the terms "first" and "second" are used to denote names rather than to indicate any specific order . Any reference signs in the claims should not be construed as limiting the scope of protection. The functions of multiple parts appearing in the claims can be implemented by a single hardware or software module. The appearance of certain technical features in different dependent claims does not mean that these technical features cannot be combined to achieve beneficial effects.

Claims

A method for pushing resource information, including:

Obtain user resource consumption information and resource provider information;

Determining the priority of the user based on the resource consumption information and the resource provider information, and determining the priority of resource information associated with the user;

Taking a user whose priority is higher than the first preset standard priority as the target user, and taking the resource information associated with the user whose priority is higher than the second preset standard priority as the target resource information;

Push the target resource information associated with the target user to the target user.
The method according to claim 1, wherein the determining the priority of the user based on the resource consumption information and the resource provider information, and determining the priority of the resource information associated with the user comprises :

Based on the resource consumption information and the resource provider information, setting the user's activity information and resource consumption potential information;

According to the activity information of the user and the resource consumption potential information, the priority of the user is determined, and the priority of the resource information associated with the user is determined.
The method according to claim 1, wherein the determining the priority of the user based on the resource consumption information and the resource provider information, and determining the priority of the resource information associated with the user comprises :

For each user, use the user's resource consumption information and the resource provider information as the input of each target decision model, and obtain the output result of each target decision model. Under the target requirements corresponding to the target decision model, the priority of the user and/or the priority of the resource information associated with the user;

Calculating the sum of the product of the output result of each target decision model and the weight of the target decision model;

The priority of the user and/or the priority of the resource information associated with the user is determined according to the sum of the products.
The method according to claim 3, further comprising:

Collecting resource consumption result information fed back by the target user after receiving the target resource information;

Update the target decision model using the resource consumption result information.
The method according to claim 1, wherein before the determining the priority of the user based on the resource consumption information and the resource provider information, and determining the priority of the resource information associated with the user ,Also includes:

The credibility calculation model is used to calculate the credibility of the resource consumption information and the credibility of the resource provider information.
The method according to claim 5, wherein the determining the priority of the user based on the resource consumption information and the resource provider information, and determining the priority of the resource information associated with the user comprises :

Based on the resource consumption information and the resource provider information, according to the credibility of the resource consumption information and the credibility of the resource provider information, determine the priority of the user, and determine the relationship with the user The priority of the associated resource information.
The method according to claim 1, further comprising:

Clustering the users to obtain at least two clusters;

For each cluster, select one of the user's resource consumption information and the resource provider information as the cluster center of the cluster;

Calculating the resource consumption information and the distance between the resource provider information and the cluster center of the users other than the user corresponding to the cluster center in the cluster;

According to the distance, the cluster and the cluster center of the cluster are updated until the updated cluster center is the same as the cluster center before the update.
The method according to claim 7, wherein the resource information includes one or more of resource providers, resource types, and resource provision solutions,

At least one item of resource information pushed to the users in the same cluster is the same.
The method according to claim 1, wherein the priority of the resource information includes resource information including one or more of the priority of the resource provider, the priority of the resource category, and the priority of the resource provision scheme.
The method according to claim 1, wherein said pushing said target resource information associated with said target user to said target user comprises:

Push the target resource information associated with the target user to the target user using real-time data streams.
The method according to any one of claims 1 to 10, wherein the resource consumption information includes one or more of the following:

User information, user resource consumption time preference information, user resource consumption resource provider preference information, user resource consumption type preference information, user resource consumption resource type preference information, user resource consumption resource provider location information, user consumption Relevance information of the resource provider of the resource.
The method according to any one of claims 1 to 10, wherein the resource provider information includes one or more of the following:

Resource provider name information, resource provider location information, resource provider location information, resource provider type information, resource provider evaluation information, resource provider popularity information, and resource provider’s resource providing relevance information.
A resource information pushing device, including:

The information acquisition module is used to acquire the user's resource consumption information and resource provider information;

A priority determining module, configured to determine the priority of the user based on the resource consumption information and the resource provider information, and determine the priority of resource information associated with the user;

The target determination module is configured to use a user with a priority higher than a first preset standard priority as a target user, and use resource information associated with the user with a priority higher than a second preset standard priority as the target resource information;

The pushing module is configured to push the target resource information associated with the target user to the target user.
The device according to claim 13, wherein the priority determining module is specifically configured to:

Based on the resource consumption information and the resource provider information, setting the user's activity information and resource consumption potential information;

According to the activity information of the user and the resource consumption potential information, the priority of the user is determined, and the priority of the resource information associated with the user is determined.
The device according to claim 13, wherein the priority determining module is specifically configured to:

For each user, use the user's resource consumption information and the resource provider information as the input of each target decision model, and obtain the output result of each target decision model. Under the target requirements corresponding to the target decision model, the priority of the user and/or the priority of the resource information associated with the user;

Calculating the sum of the product of the output result of each target decision model and the weight of the target decision model;

The priority of the user and/or the priority of the resource information associated with the user is determined according to the sum of the products.
The device according to claim 15, further comprising:

A collection module, configured to collect resource consumption result information fed back after the target user receives the target resource information;

The update module is used to update the target decision model by using the resource consumption result information.
The device according to claim 13, further comprising:

The credibility calculation module is used to use the credibility calculation model to calculate the credibility of the resource consumption information and the credibility of the resource provider information.
The device according to claim 17, wherein the priority determining module is specifically configured to:

Based on the resource consumption information and the resource provider information, according to the credibility of the resource consumption information and the credibility of the resource provider information, determine the priority of the user, and determine the relationship with the user The priority of the associated resource information.
The device according to claim 13, further comprising a clustering module, the clustering module being configured to:

Clustering the users to obtain at least two clusters;

For each cluster, select one of the user's resource consumption information and the resource provider information as the cluster center of the cluster;

Calculating the resource consumption information and the distance between the resource provider information and the cluster center of the users other than the user corresponding to the cluster center in the cluster;

According to the distance, the cluster and the cluster center of the cluster are updated until the updated cluster center is the same as the cluster center before the update.
The device according to claim 19, wherein the resource information includes one or more of resource providers, resource types, and resource provision solutions,

At least one item of resource information pushed to the users in the same cluster is the same.
The apparatus according to claim 13, wherein the priority of the resource information includes resource information including one or more of the priority of the resource provider, the priority of the resource category, and the priority of the resource provision scheme.
The device according to claim 13, wherein the pushing module is specifically configured to:

Push the target resource information associated with the target user to the target user using real-time data streams.
The device according to any one of claims 13 to 22, wherein the resource consumption information includes one or more of the following:

User information, user resource consumption time preference information, user resource consumption resource provider preference information, user resource consumption type preference information, user resource consumption resource type preference information, user resource consumption resource provider location information, user consumption Relevance information of the resource provider of the resource.
The apparatus according to any one of claims 13 to 22, wherein the resource provider information includes one or more of the following:

Resource provider name information, resource provider location information, resource provider location information, resource provider type information, resource provider evaluation information, resource provider popularity information, and resource provider’s resource providing relevance information.
A server comprising a processor, a memory, and a computer program stored on the memory and capable of running on the processor. The computer program is executed by the processor to implement any one of claims 1 to 12 The resource information push method described in item.
A computer-readable storage medium storing a computer program on the computer-readable storage medium, and when the computer program is executed by a processor, the method for pushing resource information according to any one of claims 1 to 12 is realized.