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» Search Engines that Learn from Implicit Feedback
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WWW
2008
ACM
14 years 8 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
ICMCS
2006
IEEE
144views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Using Implicit Relevane Feedback to Advance Web Image Search
Although relevance feedback has been extensively studied in content-based image retrieval in the academic area, no commercial web image search engine has employed the idea. There ...
En Cheng, Feng Jing, Mingjing Li, Wei-Ying Ma, Hai...
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
AUSAI
2007
Springer
13 years 11 months ago
Elements of a Learning Interface for Genre Qualified Search
Even prior to content, the genre of a web document leads to a first coarse binary classification of the recall space in relevant and non-relevant documents. Thinking of a genre se...
Andrea Stubbe, Christoph Ringlstetter, Randy Goebe...
SIGIR
2009
ACM
14 years 1 months ago
Segment-level display time as implicit feedback: a comparison to eye tracking
We examine two basic sources for implicit relevance feedback on the segment level for search personalization: eye tracking and display time. A controlled study has been conducted ...
Georg Buscher, Ludger van Elst, Andreas Dengel