Referral Web: combining social networks and collaborative filtering
Communications of the ACM
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Recommender systems in e-commerce
Proceedings of the 1st ACM conference on Electronic commerce
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Better control on recommender systems
CEC-EEE '06 Proceedings of the The 8th IEEE International Conference on E-Commerce Technology and The 3rd IEEE International Conference on Enterprise Computing, E-Commerce, and E-Services
Different Aspects of Social Network Analysis
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
Beyond the social search: personalizing the semantic search in social networks
OCSC'11 Proceedings of the 4th international conference on Online communities and social computing
The impact of recommender systems on item-, user-, and rating-diversity
ADMI'11 Proceedings of the 7th international conference on Agents and Data Mining Interaction
A collaborative filtering recommendation system combining semantics and Bayesian reasoning
AusDM '12 Proceedings of the Tenth Australasian Data Mining Conference - Volume 134
Supporting Social Networks With Agent-Based Services
International Journal of Virtual Communities and Social Networking
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The popularity of social networks have burgeoned in recent years. Users share and access large volumes of information on social networking sites like Facebook, Flickr, del.icio.us, etc. Whereas a few of these sites have generic, impersonal searching mechanisms, we have developed an agent-based framework that mines the social network of a user to improve search results. Our Social Network-based Item Search (SNIS) system uses agents that utilize the connections of a user in the social network to facilitate the search for items of interest. Our approach generates targeted search results that can improve the precision of the result returned from a user's query. We have implemented the SNIS agent-based framework in Flickr, a photo-sharing social network, for searching for photos by using tag lists as search queries. We discuss the architecture of SNIS, motivate the searching scheme used, and demonstrate the effectiveness of the SNIS approach by presenting results. We also show how SNIS can be utilized for expertise location.