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» Comparing relevance feedback algorithms for web search
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WWW
2008
ACM
14 years 8 months ago
Learning to rank relational objects and its application to web search
Learning to rank is a new statistical learning technology on creating a ranking model for sorting objects. The technology has been successfully applied to web search, and is becom...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
CIKM
2008
Springer
13 years 9 months ago
Matching task profiles and user needs in personalized web search
Personalization has been deemed one of the major challenges in information retrieval with a significant potential for providing better search experience to individual users. Espec...
Julia Luxenburger, Shady Elbassuoni, Gerhard Weiku...
ETRA
2010
ACM
176views Biometrics» more  ETRA 2010»
14 years 2 months ago
Learning relevant eye movement feature spaces across users
In this paper we predict the relevance of images based on a lowdimensional feature space found using several users’ eye movements. Each user is given an image-based search task,...
Zakria Hussain, Kitsuchart Pasupa, John Shawe-Tayl...
WSDM
2010
ACM
210views Data Mining» more  WSDM 2010»
14 years 5 months ago
Leveraging Temporal Dynamics of Document Content in Relevance Ranking
Many web documents are dynamic, with content changing in varying amounts at varying frequencies. However, current document search algorithms have a static view of the document con...
Jonathan L. Elsas, Susan T. Dumais
WWW
2006
ACM
14 years 8 months ago
Selective hypertext induced topic search
We address the problem of answering broad-topic queries on the World Wide Web. We present a link based analysis algorithm SelHITS, which is an improvement over Kleinberg's HI...
Amit C. Awekar, Pabitra Mitra, Jaewoo Kang