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» Search Engines that Learn from Implicit Feedback
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PKDD
2009
Springer
149views Data Mining» more  PKDD 2009»
15 years 5 months ago
Learning to Disambiguate Search Queries from Short Sessions
Web searches tend to be short and ambiguous. It is therefore not surprising that Web query disambiguation is an actively researched topic. To provide a personalized experience for ...
Lilyana Mihalkova, Raymond J. Mooney
GROUP
2005
ACM
15 years 4 months ago
Follow the (slash) dot: effects of feedback on new members in an online community
Many virtual communities involve ongoing discussions, with large numbers of users and established, if implicit rules for participation. As new users enter communities like this, b...
Cliff Lampe, Erik W. Johnston
ECML
2003
Springer
15 years 4 months ago
Optimising Performance of Competing Search Engines in Heterogeneous Web Environments
Abstract. Distributed heterogeneous search environments are an emerging phenomenon in Web search, in which topic-specific search engines provide search services, and metasearchers...
Rinat Khoussainov, Nicholas Kushmerick
103
Voted
SIGIR
2005
ACM
15 years 4 months ago
Personalizing search via automated analysis of interests and activities
We formulate and study search algorithms that consider a user’s prior interactions with a wide variety of content to personalize that user’s current Web search. Rather than re...
Jaime Teevan, Susan T. Dumais, Eric Horvitz
AAAI
2006
15 years 15 days ago
OntoSearch: A Full-Text Search Engine for the Semantic Web
OntoSearch, a full-text search engine that exploits ontological knowledge for document retrieval, is presented in this paper. Different from other ontology based search engines, O...
Xing Jiang, Ah-Hwee Tan