[Objective] Make use of the friends and historical behavior of users in social network, to recommend potential friends for the target users. [Methods] The proportion of common friends and the proportion of interaction are used as indicators to measure the closeness of the relationship in a social network graph. The relationship between friends is scored according to sociality interest and interest similarity, and the Top-k users with the highest scores are recommended to the target users. [Results] Experimental results show that the precision rate and recall rate of this method are improved significantly in comparison with traditional methods. [Limitations] Abnormal interaction without identification and treatment, may affect the accuracy of the recommendation results. [Conclusions] Considering more factors, including the proportion of interaction, the improved friend recommendation method has a better effect than traditional single factor method.
吴昊, 刘东苏. 社交网络中的好友推荐方法研究[J]. 现代图书情报技术, 2015, 31(1): 59-65.
Wu Hao, Liu Dongsu. Friend Recommendation in Social Network. New Technology of Library and Information Service, 2015, 31(1): 59-65.
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