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Sequence position recommendation method based on geographic perception

A recommendation method and sequence technology, applied in the direction of neural learning methods, electrical digital data processing, special data processing applications, etc., can solve the problems that the sparsity problem has not been well solved, and the geographic information is difficult to be fully utilized, etc., to achieve The effect of solving the data sparsity problem

Active Publication Date: 2020-09-29
长三角信息智能创新研究院
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AI Technical Summary

Problems solved by technology

However, in related research, geographic information is still difficult to be fully utilized, and the sparsity problem has not been well resolved

Method used

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  • Sequence position recommendation method based on geographic perception
  • Sequence position recommendation method based on geographic perception
  • Sequence position recommendation method based on geographic perception

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Embodiment Construction

[0057] Specific embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. It should be understood that the specific embodiments described here are only used to illustrate and explain the present invention, and are not intended to limit the present invention.

[0058] The present invention provides a sequence position recommendation method based on geographic perception, such as figure 1 As mentioned, it mainly includes the following steps:

[0059] Step 1. Crawl a certain amount of data from the location-based user service website. For a user, the data crawled includes: user ID, timestamp, location, latitude and longitude of the location.

[0060] Step 2. Based on the crawled ID information, time information, location information, and geographic location information of each user, a geo-aware sequence recommendation model based on the self-attention network is constructed, and then combined with the target location in...

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Abstract

The invention discloses a sequence position recommendation method based on geographic perception. The problem of position recommendation can be solved by fully utilizing rich metadata (user ID, timestamp, position and place longitude and latitude information) of users and historical behavior tracks. Meanwhile, the geographic perception sequence recommender GeoSAN based on the self-attention network is used for recommending the user position, compared with a traditional model, geographic information is more fully utilized, the data sparsity problem can be well solved, and the recommendation result is improved to a certain extent on multiple evaluation indexes.

Description

technical field [0001] The present invention relates to the field of machine learning and sequence position recommendation, in particular to a sequence position recommendation method based on geographic perception. Background technique [0002] With the rapid development of information technology, people's mobile behavior is easier to digitally record and share with friends. Mobile behavior can be used to understand and predict people's activity trajectories, facilitate personal daily life in terms of catering, transportation, entertainment, etc., and recommend places of interest to people. The recommended method also puts forward higher requirements. However, some existing methods cannot effectively use geographic information, and there is a problem of data sparsity, which affects the recommendation results to a certain extent. Therefore, how to make full use of the existing information to make efficient and high-quality recommendations to users is a research problem that...

Claims

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Application Information

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IPC IPC(8): G06F16/9537G06N3/04G06N3/08
CPCG06F16/9537G06N3/08G06N3/044G06N3/045Y02D10/00
Inventor 陈恩红连德富陶硕承孝敏王永璋
Owner 长三角信息智能创新研究院
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