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CHI
2007
ACM
14 years 9 months ago
An eye tracking study of the effect of target rank on web search
Web search engines present search results in a rank ordered list. This works when what a user wants is near the top, but sometimes the information that the user really wants is lo...
Zhiwei Guan, Edward Cutrell
WWW
2008
ACM
14 years 9 months ago
Ranking refinement and its application to information retrieval
We consider the problem of ranking refinement, i.e., to improve the accuracy of an existing ranking function with a small set of labeled instances. We are, particularly, intereste...
Rong Jin, Hamed Valizadegan, Hang Li
SIGIR
2009
ACM
14 years 3 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...
APWEB
2005
Springer
14 years 2 months ago
Using Probabilistic Latent Semantic Analysis for Personalized Web Search
Web users use search engine to find useful information on the Internet. However current web search engines return answer to a query independent of specific user information need. S...
Chenxi Lin, Gui-Rong Xue, Hua-Jun Zeng, Yong Yu
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