Proceedings of the 6th international conference on Intelligent user interfaces
Adaptive web search based on user profile constructed without any effort from users
Proceedings of the 13th international conference on World Wide Web
CubeSVD: a novel approach to personalized Web search
WWW '05 Proceedings of the 14th international conference on World Wide Web
Personalized Search Based on User Search Histories
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
Dogear: Social bookmarking in the enterprise
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Automatic identification of user interest for personalized search
Proceedings of the 15th international conference on World Wide Web
Mining long-term search history to improve search accuracy
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Optimizing web search using social annotations
Proceedings of the 16th international conference on World Wide Web
Can social bookmarking improve web search?
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Yes, there is a correlation: - from social networks to personal behavior on the web
Proceedings of the 17th international conference on World Wide Web
Exploring social annotations for information retrieval
Proceedings of the 17th international conference on World Wide Web
Exploring folksonomy for personalized search
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Ranking in folksonomy systems: can context help?
Proceedings of the 17th ACM conference on Information and knowledge management
Personalized social search based on the user's social network
Proceedings of the 18th ACM conference on Information and knowledge management
The demographics of web search
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
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A Social Network Service (SNS) is a type of popular, lifestyle Web service to connect a user with friends, and a user's interest in Web search can affect her friends who have similar interests. If these users' preferences can be tracked, we can show more relevant information following a user's interests. In this paper, we propose the Topic-Driven SocialRank algorithm to show interest-driven search results with relevant Web content from friends using social contacts online by identifying similar, credible users. Our assumption is that credible users issue more relevant information. We observe that a user has certain common interest with her similar friends in the SN, and focus on identifying similar users who have high credibility and sharing their search experiences. Experimental validation shows that our method significantly outperforms the baseline method. Our method is potentially effective to find more relevant search results by implicit help of familiar, credible users.