GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
The nature of statistical learning theory
The nature of statistical learning theory
On the reuse of past optimal queries
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
Automatic feedback using past queries: social searching?
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Making large-scale support vector machine learning practical
Advances in kernel methods
A re-examination of text categorization methods
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Web-collaborative filtering: recommending music by crawling the Web
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Proceedings of the 6th international conference on Intelligent user interfaces
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Query clustering using user logs
ACM Transactions on Information Systems (TOIS)
Proceedings of the 11th international conference on World Wide Web
Personalized web search by mapping user queries to categories
Proceedings of the eleventh international conference on Information and knowledge management
Ontology Based Personalized Search
ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
Implicit feedback for inferring user preference: a bibliography
ACM SIGIR Forum
Adaptive web search based on user profile constructed without any effort from users
Proceedings of the 13th international conference on World Wide Web
Further Experiments on Collaborative Ranking in Community-Based Web Search
Artificial Intelligence Review
An analysis of web searching by European AlltheWeb.com users
Information Processing and Management: an International Journal
Exploiting Query Repetition and Regularity in an Adaptive Community-Based Web Search Engine
User Modeling and User-Adapted Interaction
Context-sensitive information retrieval using implicit feedback
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Query chains: learning to rank from implicit feedback
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Personalized Search Based on User Search Histories
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
A live-user evaluation of collaborative web search
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Using probabilistic latent semantic analysis for personalized web search
APWeb'05 Proceedings of the 7th Asia-Pacific web conference on Web Technologies Research and Development
An analysis of query similarity in collaborative web search
ECIR'05 Proceedings of the 27th European conference on Advances in Information Retrieval Research
A collaborative filtering based re-ranking strategy for search in digital libraries
ICADL'05 Proceedings of the 8th international conference on Asian Digital Libraries: implementing strategies and sharing experiences
Search behavior-driven training for result re-ranking
TPDL'11 Proceedings of the 15th international conference on Theory and practice of digital libraries: research and advanced technology for digital libraries
Proceedings of the 20th ACM international conference on Information and knowledge management
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Search Engines today often return a large volume of results with possibly a few relevant results. The notion of relevance is subjective and depends on the user and the context of search. Re-ranking of these results to reflect the most relevant results to the user, using a user profile built from the relevance feedback has proved to provide good results. Our approach assumes implicit feedback gathered from a search engine query logs and learn a user profile. The user profile typically runs into sparsity problems due to the sheer volume of the WWW. Sparsity refers to the missing weights of certain words in the user profile. In this paper, we present an effective re-ranking strategy that compensates for the sparsity in a user’s profile, by applying collaborative filtering algorithms. Our evaluation results show an improvement in precision over approaches that use only a user’s profile.