Probabilistic query expansion using query logs
Proceedings of the 11th international conference on World Wide Web
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Journal of the American Society for Information Science and Technology
Optimizing web search using web click-through data
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Accurately interpreting clickthrough data as implicit feedback
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Web-page summarization using clickthrough data
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
A language model approach to keyphrase extraction
MWE '03 Proceedings of the ACL 2003 workshop on Multiword expressions: analysis, acquisition and treatment - Volume 18
ACM SIGIR Forum
From social bookmarking to social summarization: an experiment in community-based summary generation
Proceedings of the 12th international conference on Intelligent user interfaces
Extracting semantic relations from query logs
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Active exploration for learning rankings from clickthrough data
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Web search intent induction via automatic query reformulation
HLT-NAACL-Short '04 Proceedings of HLT-NAACL 2004: Short Papers
Annotation of URLs: more than the sum of parts
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
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Logfiles of search engines are a promising resource for data mining, since they provide raw data associated to users and web documents. In this paper we focus on the latter aspect and explore how the information in logfiles could be used to improve document descriptions. A pilot experiment demonstrated that document descriptors extracted from the queries that are associated with documents by clicks provide useful semantic information about documents in addition to document descriptors extracted from the full text of the web pages.