Towards interactive query expansion
SIGIR '88 Proceedings of the 11th annual international ACM SIGIR conference on Research and development in information retrieval
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Information Processing and Management: an International Journal
Journal of the American Society for Information Science
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Journal of the American Society for Information Science
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Journal of the American Society for Information Science
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Journal of the American Society for Information Science
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Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Patterns of search: analyzing and modeling Web query refinement
UM '99 Proceedings of the seventh international conference on User modeling
Real life, real users, and real needs: a study and analysis of user queries on the web
Information Processing and Management: an International Journal
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The VLDB Journal — The International Journal on Very Large Data Bases
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Journal of the American Society for Information Science and Technology
Labeling images with a computer game
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Information Processing and Management: an International Journal - Special issue: Cross-language information retrieval
Usage patterns of collaborative tagging systems
Journal of Information Science
tagging, communities, vocabulary, evolution
CSCW '06 Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work
Analysis of multiple query reformulations on the web: The interactive information retrieval context
Information Processing and Management: an International Journal
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In the traditional model of information retrieval, searchers and indexers choose query and index terms, respectively, and these term choices are ultimately compared in a matching process. One of the main challenges in information science and information retrieval is that searchers and indexers often do not choose the same term even though the item is relevant to the need whereas at other times they do choose the same term even though it is not relevant. But if both searchers and indexers have the opportunity to review feedback data showing the success or failure of their previous term choices, then there exists an evolutionary force that, all else being equal, will lead to helpful convergence in searchers' and indexers' term usage when the information is relevant, and helpful divergence of term usage when it is not. Based on learning theory, and new theory presented here, it is possible to predict which terms will emerge as the terminological conventions that are used by groups of searchers and the indexers of relevant and nonrelevant information items. © 2009 Wiley Periodicals, Inc.