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CIKM
2007
Springer
14 years 4 months ago
Expertise drift and query expansion in expert search
Pseudo-relevance feedback, or query expansion, has been shown to improve retrieval performance in the adhoc retrieval task. In such a scenario, a few top-ranked documents are assu...
Craig Macdonald, Iadh Ounis
SIGIR
2005
ACM
14 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...
AAAI
2012
12 years 14 days ago
Improving Twitter Retrieval by Exploiting Structural Information
Most Twitter search systems generally treat a tweet as a plain text when modeling relevance. However, a series of conventions allows users to tweet in structural ways using combin...
Zhunchen Luo, Miles Osborne, Sasa Petrovic, Ting W...
JCDL
2010
ACM
188views Education» more  JCDL 2010»
14 years 3 months ago
Exposing the hidden web for chemical digital libraries
In recent years, the vast amount of digitally available content has lead to the creation of many topic-centered digital libraries. Also in the domain of chemistry more and more di...
Sascha Tönnies, Benjamin Köhncke, Oliver...
SIGIR
2009
ACM
14 years 4 months ago
Query dependent pseudo-relevance feedback based on wikipedia
Pseudo-relevance feedback (PRF) via query-expansion has been proven to be effective in many information retrieval (IR) tasks. In most existing work, the top-ranked documents from...
Yang Xu, Gareth J. F. Jones, Bin Wang