Friend recommendation system and method based on community detection

Abstract

The invention belongs to the technical field of big data and a data mining recommendation system, and particularly relates to a friend recommendation system and method based on community detection. The system comprises five modules, including a data acquisition module, a data processing module, a data storage module, a business logic module and a display module. The invention also puts forward a calculation method based on community detection. The method comprises the following steps that: according to the signed geographic position information and the common friend number of a user, calculating a user distance similarity and an acquaintance degree; adding into an LMF (Latent Factor Model) algorithm to carry out community division; in a generated friend community, according to user discrete sign in time, adopting a kernel density estimation algorithm to calculate the 24-h integral sign in probability density of the user; and then, calculating the site similarity of the user sign in site, and establishing a user space-time similarity implementation model. By use of the system, the problem that recommendation operation complexity is increased due to a user interest diversity recommendation problem and constantly changing user interests can be solved. Compared with the traditional recommendation technology, the system is characterized in that the technology is more flexibly recommended, and recommendation quality is improved.

Description

technical field [0001] The present invention designs a big data data mining recommendation system technical field, especially a friend recommendation system and method based on community discovery. Background technique [0002] Internet users are playing more and more active roles, especially the development of location-based services and mobile social networks, which makes the connection between users more closely and widely increases people's social circle. It is more and more obvious that users tend to use mobile smart terminals. Social software such as WeChat, Weibo and FaceBook all have corresponding mobile terminals, and can share current location information and give corresponding comments in real time. The mobile social network has the characteristics of both social network and mobile network, creating a new way of socializing and bringing the network and reality closer. The main feature of the mobile social network is that the geographical location is added. Users ...

AI Technical Summary

Problems solved by technology

Due to the huge scale of POIs, the number of POIs visited by each user is limited, and each person's interests and habits are different, which also brings new challenges to the user's friend recommendation problem.

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