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» Linguistic Knowledge can Improve Information Retrieval
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AND
2010
15 years 4 months ago
Statement map: reducing web information credibility noise through opinion classification
On the Internet, users often encounter noise in the form of spelling errors or unknown words, however, dishonest, unreliable, or biased information also acts as noise that makes i...
Koji Murakami, Eric Nichols, Junta Mizuno, Yotaro ...
FLAIRS
2001
15 years 8 months ago
Integrating Task, Role, and User Modeling in Organizational Memories
In application areas like personal information agents user modelstypically maintain sophisticated representations of personal interest profiles. Theserepresentations can be utiliz...
Ludger van Elst, Andreas Abecker
MM
2005
ACM
171views Multimedia» more  MM 2005»
16 years 3 days ago
Semantic manifold learning for image retrieval
Learning the user’s semantics for CBIR involves two different sources of information: the similarity relations entailed by the content-based features, and the relevance relatio...
Yen-Yu Lin, Tyng-Luh Liu, Hwann-Tzong Chen
CLEF
2008
Springer
15 years 8 months ago
Combining Logic and Machine Learning for Answering Questions
Abstract. LogAnswer is a logic-oriented question answering system developed by the AI research group at the University of Koblenz-Landau and by the IICS at the University of Hagen....
Ingo Glöckner, Björn Pelzer
WWW
2004
ACM
16 years 7 months ago
Understanding user goals in web search
Previous work on understanding user web search behavior has focused on how people search and what they are searching for, but not why they are searching. In this paper, we describ...
Daniel E. Rose, Danny Levinson