Communications of the ACM
ACM SIGIR Forum
Using annotations in enterprise search
Proceedings of the 15th international conference on World Wide Web
Optimizing web search using social annotations
Proceedings of the 16th 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
Reducing long queries using query quality predictors
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Personalized social search based on the user's social network
Proceedings of the 18th ACM conference on Information and knowledge management
Web search personalization via social bookmarking and tagging
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Modern Information Retrieval
Lucene in Action, Second Edition: Covers Apache Lucene 3.0
Lucene in Action, Second Edition: Covers Apache Lucene 3.0
Personalized social query expansion using social bookmarking systems
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Personalizing web search with folksonomy-based user and document profiles
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Using social annotations to enhance document representation for personalized search
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Sopra: a new social personalized ranking function for improving web search
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
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In this paper, we introduce LAICOS, a social Web search engine as a contribution to the growing area of Social Information Retrieval (SIR). Social information and personalization are at the heart of LAICOS. On the one hand, the social context of documents is added as a layer to their textual content traditionally used for indexing to provide Personalized Social Document Representations. On the other hand, the social context of users is used for the query expansion process using the Personalized Social Query Expansion framework (PSQE) proposed in our earlier works. We describe the different components of the system while relying on social bookmarking systems as a source of social information for personalizing and enhancing the IR process. We show how the internal structure of indexes as well as the query expansion process operated using social information.