Recommendation method for next interest point of social network

A technology of social network and recommendation method, applied in the fields of instruments, data processing applications, digital data information retrieval, etc., can solve the problems of data sparseness and difficulty in recommendation, and achieve the effect of strong parallel computing ability and reducing computing complexity.

Active Publication Date: 2021-08-03
GUANGXI NORMAL UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention aims to solve the problem of difficulty in recommending the next point of interest in a social network due to sparse data, and provides a method for recommending the next point of interest in a social network

Method used

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  • Recommendation method for next interest point of social network
  • Recommendation method for next interest point of social network
  • Recommendation method for next interest point of social network

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Embodiment Construction

[0026] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with specific examples.

[0027] Generally speaking, the user's past historical trajectory shows the user's preference. First of all, since users show different preferences of users at different times. For example, the user may prefer POIs near the company during weekdays; on weekends, the user may prefer POIs near home. At the same time, users also show different interest preferences in different time ranges of the day. For example, during tea time, the user may choose a leisure POI such as a coffee shop; during dinner time, the user may choose to go to a POI such as a bar after dinner. So, users show different preferences at different times. Therefore, the present invention uses the Transformer model to learn complex and diverse long-term preferences of users. Secondly, since the user's rece...

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Abstract

The invention discloses a recommendation method for a next interest point of a social network, and the method comprises the steps: obtaining a centralized representation of a preference interest point of a user through an encoder layer of a Transform; secondly, sending the obtained centralized representation of the user preference interest points to a divided time window; then, aiming at different interest preference distributions of the same user in different time windows, endowing different weights in different time windows, and obtaining a preference interest point state of the user according to the obtained weights; finally, filtering out candidate POIs from all the POIs according to geographical factor information and merchant popularity, calculating scores of the candidate POIs based on the preference interest point state of the user, and recommending Top_k POIs to the user. According to the method, the problem that recommendation of the next interest point of the social network is difficult due to sparse data can be solved.

Description

technical field [0001] The invention relates to the technical field, in particular to a method for recommending a next point of interest in a social network. Background technique [0002] Next point of interest (POI) recommendation is an important aspect of the feed of information for location-based social networks, which aims to predict the POI that the user will visit next based on the user's check-in records. Compared with the general point of interest recommendation, the data of social network is more sparse, because a person has few user behaviors, so it is more difficult to understand the recommendation of the user's next point of interest; in addition, the prediction of the next point of interest in social network It must be continuous based on the current user's location. [0003] In recent years, people have done a lot of research on the recommendation of the next point of interest, and RNN is widely used, and its performance is particularly outstanding in the reco...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q50/00G06Q10/06G06F16/9535G06F16/9536G06F16/9537
CPCG06Q50/01G06Q10/06393G06F16/9535G06F16/9536G06F16/9537
Inventor 郭燕鸽梁媛刘鹏
Owner GUANGXI NORMAL UNIV
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