Mining web search user behavior to enhance web search relevance
作者： Robert J. Ragno , Eric D. Brill , Yevgeny E. Agichtein , Susan T. Dumais
DOI:
关键词: Relevance (information retrieval) 、 Collective behavior 、 User modeling 、 Information retrieval 、 Component (UML) 、 Computer user satisfaction 、 Search engine 、 Unique user 、 Computer science 、 User interface
摘要: Systems and methods that estimate user preference, via automatic interpretation of behavior. A behavior component associated with a search engine can automatically interpret collective users (e.g., web users). Such feedback include features predictive models from component) are robust to noise, which be present in observed interactions the results malicious and/or irrational activity.).
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