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» Term Ranking for Clustering Web Search Results
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ICDE
2008
IEEE
241views Database» more  ICDE 2008»
14 years 9 months ago
PictureBook: A Text-and-Image Summary System for Web Search Result
Search engine technology plays an important role in Web information retrieval. However, with Internet information explosion, traditional searching techniques cannot provide satisfa...
Baile Shi, Guoyu Hao, Hongtao Xu, Mei Wang, Qi Zha...
CIKM
2010
Springer
13 years 5 months ago
Web search solved?: all result rankings the same?
The objective of this work is to derive quantitative statements about what fraction of web search queries issued to the state-of-the-art commercial search engines lead to excellen...
Hugo Zaragoza, Berkant Barla Cambazoglu, Ricardo A...
SIGIR
2009
ACM
14 years 2 months ago
Smoothing clickthrough data for web search ranking
Incorporating features extracted from clickthrough data (called clickthrough features) has been demonstrated to significantly improve the performance of ranking models for Web sea...
Jianfeng Gao, Wei Yuan, Xiao Li, Kefeng Deng, Jian...
KDD
2006
ACM
167views Data Mining» more  KDD 2006»
14 years 8 months ago
Identifying "best bet" web search results by mining past user behavior
The top web search result is crucial for user satisfaction with the web search experience. We argue that the importance of the relevance at the top position necessitates special h...
Eugene Agichtein, Zijian Zheng
WWW
2011
ACM
13 years 2 months ago
Parallel boosted regression trees for web search ranking
Gradient Boosted Regression Trees (GBRT) are the current state-of-the-art learning paradigm for machine learned websearch ranking — a domain notorious for very large data sets. ...
Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal...