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» Search Engines: Information Retrieval in Practice
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IPM
2008
100views more  IPM 2008»
14 years 9 months ago
Query-level loss functions for information retrieval
Many machine learning technologies such as support vector machines, boosting, and neural networks have been applied to the ranking problem in information retrieval. However, since...
Tao Qin, Xu-Dong Zhang, Ming-Feng Tsai, De-Sheng W...
CIKM
2008
Springer
14 years 11 months ago
Understanding the relationship between searchers' queries and information goals
We describe results from Web search log studies aimed at elucidating user behaviors associated with queries and destination URLs that appear with different frequencies. We note th...
Doug Downey, Susan T. Dumais, Daniel J. Liebling, ...
JUCS
2007
94views more  JUCS 2007»
14 years 9 months ago
Discovering the Semantics of User Keywords
Abstract: The technology in the field of digital media generates huge amounts of textual information every day, so mechanisms to retrieve relevant information are needed. Under th...
Raquel Trillo, Jorge Gracia, Mauricio Espinoza, Ed...
SIGIR
2005
ACM
15 years 3 months ago
Predicting query difficulty on the web by learning visual clues
We describe a method for predicting query difficulty in a precision-oriented web search task. Our approach uses visual features from retrieved surrogate document representations (...
Eric C. Jensen, Steven M. Beitzel, David A. Grossm...
WWW
2009
ACM
15 years 10 months ago
Search result re-ranking based on gap between search queries and social tags
Both search engine click-through log and social annotation have been utilized as user feedback for search result re-ranking. However, to our best knowledge, no previous study has ...
Jun Yan, Ning Liu, Elaine Qing Chang, Lei Ji, Zhen...