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» Comparing relevance feedback algorithms for web search
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ETRA
2010
ACM
197views Biometrics» more  ETRA 2010»
14 years 2 months ago
Image ranking with implicit feedback from eye movements
In order to help users navigate an image search system, one could provide explicit information on a small set of images as to which of them are relevant or not to their task. Thes...
David R. Hardoon, Kitsuchart Pasupa
CIKM
2008
Springer
13 years 9 months ago
Modeling multi-step relevance propagation for expert finding
An expert finding system allows a user to type a simple text query and retrieve names and contact information of individuals that possess the expertise expressed in the query. Thi...
Pavel Serdyukov, Henning Rode, Djoerd Hiemstra
CSE
2009
IEEE
14 years 2 months ago
Web Science 2.0: Identifying Trends through Semantic Social Network Analysis
—We introduce a novel set of social network analysis based algorithms for mining the Web, blogs, and online forums to identify trends and find the people launching these new tren...
Peter A. Gloor, Jonas Krauss, Stefan Nann, Kai Fis...
MIR
2006
ACM
145views Multimedia» more  MIR 2006»
14 years 1 months ago
Similarity learning via dissimilarity space in CBIR
In this paper, we introduce a new approach to learn dissimilarity for interactive search in content based image retrieval. In literature, dissimilarity is often learned via the fe...
Giang P. Nguyen, Marcel Worring, Arnold W. M. Smeu...
JMLR
2010
141views more  JMLR 2010»
13 years 2 months ago
Pinview: Implicit Feedback in Content-Based Image Retrieval
This paper describes Pinview, a content-based image retrieval system that exploits implicit relevance feedback during a search session. Pinview contains several novel methods that...
Peter Auer, Zakria Hussain, Samuel Kaski, Arto Kla...