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» Predicting query reformulation during web searching
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KDD
2005
ACM
177views Data Mining» more  KDD 2005»
16 years 1 days ago
Query chains: learning to rank from implicit feedback
This paper presents a novel approach for using clickthrough data to learn ranked retrieval functions for web search results. We observe that users searching the web often perform ...
Filip Radlinski, Thorsten Joachims
IJCAI
2007
15 years 1 months ago
Learning User Clicks in Web Search
Machine learning for predicting user clicks in Webbased search offers automated explanation of user activity. We address click prediction in the Web search scenario by introducing...
Ding Zhou, Levent Bolelli, Jia Li, C. Lee Giles, H...
SIGIR
2005
ACM
15 years 5 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...
CIKM
2008
Springer
15 years 1 months ago
A survey of pre-retrieval query performance predictors
The focus of research on query performance prediction is to predict the effectiveness of a query given a search system and a collection of documents. If the performance of queries...
Claudia Hauff, Djoerd Hiemstra, Franciska de Jong
SEMWEB
2009
Springer
15 years 6 months ago
Learning Semantic Query Suggestions
An important application of semantic web technology is recognizing human-defined concepts in text. Query transformation is a strategy often used in search engines to derive querie...
Edgar Meij, Marc Bron, Laura Hollink, Bouke Huurni...