Extended Boolean information retrieval
Communications of the ACM
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Exploiting hierarchical domain structure to compute similarity
ACM Transactions on Information Systems (TOIS)
The link prediction problem for social networks
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Trust and nuanced profile similarity in online social networks
ACM Transactions on the Web (TWEB)
Using twitter to recommend real-time topical news
Proceedings of the third ACM conference on Recommender systems
Structural and Message Based Private Friend Recommendation
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
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As the wide popularization of online social networks, online users are not content only with keeping online friendship with social friends in real life any more. They hope the system designers can help them exploring new friends with common interest. However, the large amount of online users and their diverse and dynamic interests possess great challenges to support such a novel feature in online social networks. In this paper, by leveraging interest-based features, we design a general friend recommendation framework, which can characterize user interest in two dimensions: context (location, time) and content, as well as combining domain knowledge to improve recommending quality. We also design a potential friend recommender system in a real online social network of biology field to show the effectiveness of our proposed framework.