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» Query chains: learning to rank from implicit feedback
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WWW
2008
ACM
15 years 10 months ago
Mining the search trails of surfing crowds: identifying relevant websites from user activity
The paper proposes identifying relevant information sources from the history of combined searching and browsing behavior of many Web users. While it has been previously shown that...
Mikhail Bilenko, Ryen W. White
CONTEXT
2007
Springer
15 years 3 months ago
Discovering Hidden Contextual Factors for Implicit Feedback
Abstract. This paper presents a statistical framework based on Principal Component Analysis (PCA) for discovering the contextual factors which most strongly influence user behavio...
Massimo Melucci, Ryen W. White
CIKM
2009
Springer
15 years 4 months ago
Enabling multi-level relevance feedback on pubmed by integrating rank learning into DBMS
Background: Finding relevant articles from PubMed is challenging because it is hard to express the user’s specific intention in the given query interface, and a keyword query ty...
Hwanjo Yu, Taehoon Kim, Jinoh Oh, Ilhwan Ko, Sungc...
SIGIR
2002
ACM
14 years 9 months ago
Finding relevant documents using top ranking sentences: an evaluation of two alternative schemes
In this paper we present an evaluation of techniques that are designed to encourage web searchers to interact more with the results of a web search. Two specific techniques are ex...
Ryen White, Ian Ruthven, Joemon M. Jose
VLDB
2007
ACM
137views Database» more  VLDB 2007»
15 years 3 months ago
Detecting Attribute Dependencies from Query Feedback
Real-world datasets exhibit a complex dependency structure among the data attributes. Learning this structure is a key task in automatic statistics configuration for query optimi...
Peter J. Haas, Fabian Hueske, Volker Markl