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Final year IEEE projects 2016 based on Java IN Multimedia (Social Networking)
  • Final year IEEE projects 2016 based on Java IN Multimedia (Social Networking)

Social Friend Recommendation Based on Multiple Network Correlation

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Social Friend Recommendation Based Multiple Network Correlation

In social media, Friend recommendation is an important recommender application.Social Friend Recommendation Based Multiple Network Correlation.

Major social websites such as Twitter and Facebook are all capable of recommending friends to individuals. However, most of these websites use simple friend recommendation algorithms such as similarity, popularity, or “friend’s friends are friends,” which are intuitive but consider few of the characteristics of the social network.

Social Friend Recommendation Based Multiple Network Correlation. The proposed system investigates the structure of social networks and develop an algorithm for network correlation-based social friend recommendation i.e., NC-based SFR. To accomplish this goal, different “social role” networks are correlated, their relationships are identified and friend recommendations are made. NC-based SFR is characterized by two key components:

1)the network structure should be maximally preserved before and after network alignment, and

2) related networks are aligned by selecting important features from each network. After important feature selection has been made, friends based on these features are recommended.

Experiments are conducted on the Flickr network, which contains more than ten thousand nodes and over 30 thousand tags covering half a million photos, to show that the proposed algorithm recommends friends more precisely than reference methods.

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