Interest Recommendation Method Based on Geography-Society Relationship and Deep Implicit Interest Mining

A technology of social relations and recommendation methods, applied in the Internet field, can solve problems such as unsatisfactory accuracy rate

Active Publication Date: 2019-03-12
安徽十锎信息科技有限公司
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AI Technical Summary

Problems solved by technology

However, so far, no research has taken into account the impact of dual geo-social relationships and deep implicit interest topic similarity on the recommenda

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  • Interest Recommendation Method Based on Geography-Society Relationship and Deep Implicit Interest Mining
  • Interest Recommendation Method Based on Geography-Society Relationship and Deep Implicit Interest Mining
  • Interest Recommendation Method Based on Geography-Society Relationship and Deep Implicit Interest Mining

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Embodiment Construction

[0034] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0035] Before introducing the detailed technical scheme of the present invention, the following definitions are first proposed:

[0036] Definition 1: Point of interest recommendation. In a location-based social network, a point of interest is defined as a specific event or place with a unique identifier. It is stipulated that a point of interest has three attributes: identifier, location and content of the point of interest. Use p to id...

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Abstract

The invention discloses an interest recommendation method based on geography-society relationship and deep implicit interest mining, which relates to the technical field of the Internet. Under the current reachable area of users, a deep potential geography-social relations point of interest recommendation model DDR-RP is established based on the similarity between the user's co-sign-in behavior and the user's implicit interest topic according to the user's link relationship. In the user-reachable area, the user link relationship and the user co-sign-in behavior relationship are aggregated intodouble-geography-society relationship and the proposed RTU-TCP method is used for mining users' deep implicit interest topic similarity relationship. The similarity relation of the double-geography-society relationship and Deep Implicit Interest Topic serves as the regularization term of DDR-PR model to improve the performance of POI recommendation method. The results show that DDR-PR model is superior to other benchmark recommendation methods in two real datasets.

Description

Technical field [0001] The invention relates to the field of Internet technology, in particular to a method for recommending points of interest based on geographic-social relations and deep implicit interest mining. Background technique [0002] With the widespread application of mobile devices, location acquisition and wireless communication technologies and the rapid development of Web 2.0 technology, location-based social networking platforms Foursquare, Gowalla, Yelp, and Facebook Places have attracted hundreds of millions of users. Points of interest are recommended (POI Recommendation) has become a hot research field. Point-of-interest recommendation can not only satisfy users' personalized preferences for visiting new places, but also help LBSNs provide users with more accurate location services to increase turnover, opening a new paradigm research that combines spatial and social dimensions. [0003] Currently, there is a lot of research work in point of interest recommend...

Claims

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Application Information

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IPC IPC(8): G06F16/9537G06Q50/00
CPCG06Q50/01
Inventor 崔琳汪材印张志伟潘正高吴孝银刘永清
Owner 安徽十锎信息科技有限公司
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