Friend recommendation system based on user sign-in similarity

A friend recommendation and recommendation system technology, applied in transmission systems, digital transmission systems, special data processing applications, etc., can solve the problem of not fully considering the user's hobbies or behavior patterns.

Inactive Publication Date: 2014-01-01
北京中实信息技术有限公司
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Problems solved by technology

This method does not fully consider the user's overall hobbies or behavior patterns

Method used

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  • Friend recommendation system based on user sign-in similarity
  • Friend recommendation system based on user sign-in similarity
  • Friend recommendation system based on user sign-in similarity

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Embodiment

[0083] see figure 1 , figure 2 As shown, it is assumed that there are 4 (ie b=4) sign-in users in the LBSN database 300, namely user BU 1 , user BU 2 , user BU 3 , user BU 4 , and these check-in users are not friends before making interest recommendations. pm in LBSN database 1 For hospital points of interest, pm 2 For college points of interest, pm 3 Points of interest for office buildings, pm 4 Point of interest for the mall, pm 5 For car park points of interest, pm 6is the point of interest of the hotel, that is, q=6. Each point of interest is also a theme. Under the condition that the number of preset topics is t=2 and the number of points of interest is v=3, the system of the present invention is used to recommend friends based on the similarity of user check-ins.

[0084] Sign in user BU 1 The points of interest to sign in are pm 1 、pm 2 、pm 3 、pm 4 、pm 5 , sign in user BU 1 of check-ins Respectively 2 times, 3 times, 1 time, 4 times, 5 times.

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Abstract

The invention discloses a friend recommendation system based on user sign-in similarity. The friend recommendation system comprises an interest recommendation module, a similarity computation module and a theme extraction module. Firstly, sign-in records of previous users are obtained from an LBSN (Location Based Social Network) database through the theme extraction module, and a potential theme in the extracted sign-in records of the users is obtained through a theme extraction algorithm; secondly, by using the potential theme extracted through the theme extraction module, similarity of each user in a candidate user set and a request user under each theme is respectively calculated through calling a computing method of the similarity computation module; thirdly, summing the similarity of each user under each theme so as to obtain a final similarity; lastly, determining a final recommendation friend by the interest recommendation module through request parameter setting of the request user, and returning to the request user.

Description

technical field [0001] The present invention relates to a friend recommendation system, more particularly, refers to a system that calculates the user's similarity based on the user's past check-in records, and recommends friends according to the user's similarity. The system of the invention belongs to the technical field of friend recommendation in a location-based social network. Background technique [0002] Social network service providers have different positioning for different groups of people. For example, the original social networking sites were used to make friends, such as Friendster and Linkedin in the United States. There are also websites that provide services for business people to make friends, such as China's Tianji.com and Germany's OPENBC. Some social networking sites for business people also have the function of job search and recruitment. But the sites with the greatest profit prospects are dating and dating sites. These sites already have millions...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30H04L12/58
CPCG06F16/9535G06F16/9537
Inventor 李巍蒋江涛李云春李国君
Owner 北京中实信息技术有限公司
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