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» Extraction of user preferences from a few positive documents
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WWW
2010
ACM
14 years 1 months ago
Sampling high-quality clicks from noisy click data
Click data captures many users’ document preferences for a query and has been shown to help significantly improve search engine ranking. However, most click data is noisy and of...
Adish Singla, Ryen W. White
SIGIR
2008
ACM
13 years 6 months ago
Bilingual topic aspect classification with a few training examples
This paper explores topic aspect (i.e., subtopic or facet) classification for English and Chinese collections. The evaluation model assumes a bilingual user who has found document...
Yejun Wu, Douglas W. Oard
ICDE
2008
IEEE
189views Database» more  ICDE 2008»
14 years 21 days ago
Adapting ranking functions to user preference
— Learning to rank has become a popular method for web search ranking. Traditionally, expert-judged examples are the major training resource for machine learned web ranking, whic...
Keke Chen, Ya Zhang, Zhaohui Zheng, Hongyuan Zha, ...
CIKM
2008
Springer
13 years 8 months ago
Intra-document structural frequency features for semi-supervised domain adaptation
In this work we try to bridge the gap often encountered by researchers who find themselves with few or no labeled examples from their desired target domain, yet still have access ...
Andrew Arnold, William W. Cohen
DEBU
2006
112views more  DEBU 2006»
13 years 6 months ago
Web Information Extraction and User Modeling: Towards Closing the Gap
Web search engines have become the primary method of accessing information on the web. Billions of queries are submitted to major web search engines, reflecting a wide range of in...
Eugene Agichtein