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» Optimizing search engines using clickthrough data
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WWW
2005
ACM
14 years 8 months ago
CubeSVD: a novel approach to personalized Web search
As the competition of Web search market increases, there is a high demand for personalized Web search to conduct retrieval incorporating Web users' information needs. This pa...
Jian-Tao Sun, Hua-Jun Zeng, Huan Liu, Yuchang Lu, ...
CIKM
2009
Springer
13 years 8 months ago
Improving search engines using human computation games
Work on evaluating and improving the relevance of web search engines typically use human relevance judgments or clickthrough data. Both these methods look at the problem of learni...
Hao Ma, Raman Chandrasekar, Chris Quirk, Abhishek ...
KDD
2008
ACM
176views Data Mining» more  KDD 2008»
14 years 8 months ago
Context-aware query suggestion by mining click-through and session data
Query suggestion plays an important role in improving the usability of search engines. Although some recently proposed methods can make meaningful query suggestions by mining quer...
Huanhuan Cao, Daxin Jiang, Jian Pei, Qi He, Zhen L...
CIKM
2008
Springer
13 years 9 months ago
Are click-through data adequate for learning web search rankings?
Learning-to-rank algorithms, which can automatically adapt ranking functions in web search, require a large volume of training data. A traditional way of generating training examp...
Zhicheng Dou, Ruihua Song, Xiaojie Yuan, Ji-Rong W...
TKDE
2008
231views more  TKDE 2008»
13 years 7 months ago
Personalized Concept-Based Clustering of Search Engine Queries
A major problem of current Web search is that search queries are usually short and ambiguous, and thus are insufficient for specifying the precise user needs. To alleviate this pro...
Kenneth Wai-Ting Leung, Wilfred Ng, Dik Lun Lee