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CIKM
2007
Springer
15 years 9 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
15 years 8 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
13 years 5 months 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»
15 years 8 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
15 years 9 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