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» Term Ranking for Clustering Web Search Results
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KDD
2005
ACM
177views Data Mining» more  KDD 2005»
14 years 9 months ago
Query chains: learning to rank from implicit feedback
This paper presents a novel approach for using clickthrough data to learn ranked retrieval functions for web search results. We observe that users searching the web often perform ...
Filip Radlinski, Thorsten Joachims
ADC
2009
Springer
113views Database» more  ADC 2009»
14 years 3 months ago
Ranking-Constrained Keyword Sequence Extraction from Web Documents
Given a large volume of Web documents, we consider problem of finding the shortest keyword sequences for each of the documents such that a keyword sequence can be rendered to a g...
Ding-Yi Chen, Xue Li, Jing Liu, Xia Chen
WWW
2007
ACM
14 years 9 months ago
Answering relationship queries on the web
Finding relationships between entities on the Web, e.g., the connections between different places or the commonalities of people, is a novel and challenging problem. Existing Web ...
Gang Luo, Chunqiang Tang, Ying-li Tian
WWW
2009
ACM
14 years 9 months ago
An axiomatic approach for result diversification
Understanding user intent is key to designing an effective ranking system in a search engine. In the absence of any explicit knowledge of user intent, search engines want to diver...
Sreenivas Gollapudi, Aneesh Sharma
WWW
2005
ACM
14 years 9 months ago
Identifying link farm spam pages
With the increasing importance of search in guiding today's web traffic, more and more effort has been spent to create search engine spam. Since link analysis is one of the m...
Baoning Wu, Brian D. Davison