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Entity push method and system

An entity, to-be-pushed technology, applied in the field of electronic information, can solve the problems of blindness, inability to accurately describe the preferences of user entities, randomness and error in data, etc., and achieve the effect of improving click-through rate.

Active Publication Date: 2021-04-27
KOU KOU XIANG CHUAN BEIJING NETWORK TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, in the process of implementing the present invention, the inventor found that there are at least the following problems in the prior art: first, the user's online browsing behavior is free, resulting in a lot of user's online browsing behavior data being random and Second, although the user's online and offline payment behavior data overcomes the arbitrariness and error of online browsing behavior data, the user has blindness in the selection of entities in areas he is not familiar with, so the above two behaviors are used to Data does not accurately describe user preferences for entities
This shows, lacks a kind of method that can solve the above problem well in the prior art

Method used

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  • Entity push method and system

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Experimental program
Comparison scheme
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Embodiment 1

[0062] figure 1 It shows a flow chart of an entity push method provided by Embodiment 1 of the present invention. In this embodiment, APP is taken as an example for illustration. Of course, the solution of the present invention can also be applied to other scenarios, and the present invention does not limit this . Among them, entities refer to: things that exist objectively and can be distinguished from each other, specifically including commodities, stores, coupons, store visit articles, etc. The entity in this embodiment is mainly described by taking a store as an example.

[0063] Such as figure 1 As shown, the method includes:

[0064] Step S110: Obtain the user attribute information of the current user and the entity attribute information of each entity to be pushed.

[0065] Specifically, how to describe a user is one of the problems to be solved by the recommendation algorithm. In this embodiment, user attribute information is used to describe a user, wherein the us...

Embodiment 3

[0103] image 3 It shows a schematic structural diagram of an entity push system provided by Embodiment 3 of the present invention, and the system includes:

[0104] The acquisition module 31 is adapted to acquire the user attribute information of the current user and the entity attribute information of each entity to be pushed;

[0105] The feature vector generation module 32 is adapted to generate a feature vector corresponding to the entity to be pushed according to the entity attribute information and user attribute information of the entity to be pushed for each entity to be pushed;

[0106] The push module 33 is adapted to input the feature vector of each entity to be pushed into a preset entity evaluation model, and push the entity for the current user according to the output result of the entity evaluation model; Interaction behavior between entities is determined.

[0107] Optionally, the acquisition module 31 is further adapted to: acquire environmental attribute i...

Embodiment 4

[0129] Embodiment 4 of the present application provides a non-volatile computer storage medium, the computer storage medium stores at least one executable instruction, and the computer executable instruction can execute the entity pushing method in any of the above method embodiments.

[0130] Specifically, the executable instructions may be used to make the processor perform the following operations: obtain user attribute information of the current user and entity attribute information of each entity to be pushed; The attribute information generates a feature vector corresponding to the entity to be pushed; input the feature vector of each entity to be pushed into the preset entity evaluation model, and push the entity for the current user according to the output result of the entity evaluation model; wherein, the entity evaluation model is based on each The interactive behavior between the sample user and the sample entity in the familiar area is determined.

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Abstract

The invention discloses an entity push method and system, which relate to the field of electronic information. The method includes: obtaining user attribute information of the current user and entity attribute information of each entity to be pushed; The entity attribute information and user attribute information of the entity generate a feature vector corresponding to the entity to be pushed; input the feature vector of each entity to be pushed into the preset entity evaluation model, and push the entity for the current user according to the output result of the entity evaluation model, Wherein, the entity evaluation model is determined according to the interaction behavior between each sample user and the sample entity in the familiar area. According to this method, the entity evaluation model can be constructed by using the interaction between the user and the sample entity in the familiar area, and the user's entity preference can be predicted by using the model and attribute information of multiple dimensions, so that the accuracy of the prediction result is more accurate. High, and then push entities to users in a targeted manner.

Description

technical field [0001] The invention relates to the field of electronic information, in particular to an entity push method and system. Background technique [0002] O2O (Online to Offline, online and offline) refers to the use of the Internet to realize the combination of offline consumption resources and online. It is an important traffic guidance strategy and channel for O2O platforms to recommend offline entities to users online. In order to improve the user click rate, a model is needed to describe the user's interest in the entity. [0003] In one application scenario, the O2O recommendation algorithm is modeled based on the user's online browsing behavior data and online and offline payment behavior data. The user's online browsing behavior data mainly includes: (1) the user's search behavior data using keyword search or category search and the click behavior on the search result page; (2) the user's click behavior on the entity information recommended to him by the...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q30/02
CPCG06Q30/0224G06Q30/0252G06Q30/0256
Inventor 张小威
Owner KOU KOU XIANG CHUAN BEIJING NETWORK TECH CO LTD
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