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» Learning from Logged Implicit Exploration Data
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CIKM
2009
Springer
14 years 1 months ago
Exploring relevance for clicks
Mining feedback information from user click-through data is an important issue for modern Web retrieval systems in terms of architecture analysis, performance evaluation and algor...
Rongwei Cen, Yiqun Liu, Min Zhang, Bo Zhou, Liyun ...
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
14 years 7 months ago
Practical learning from one-sided feedback
In many data mining applications, online labeling feedback is only available for examples which were predicted to belong to the positive class. Such applications include spam filt...
D. Sculley
ECAI
2008
Springer
13 years 9 months ago
Extracting Semantic Annotations from Moodle Data
The purpose of this paper is to provide a solution which allows automatic reasoning processes over Moodle activities logs, in order to obtain user-personalized recommendations. Act...
Mihai Gabroveanu, Ion-Mircea Diaconescu
WWW
2010
ACM
14 years 2 months ago
Optimal rare query suggestion with implicit user feedback
Query suggestion has been an effective approach to help users narrow down to the information they need. However, most of existing studies focused on only popular/head queries. Si...
Yang Song, Li-wei He
WWW
2009
ACM
14 years 8 months ago
Towards context-aware search by learning a very large variable length hidden markov model from search logs
Capturing the context of a user's query from the previous queries and clicks in the same session may help understand the user's information need. A context-aware approac...
Huanhuan Cao, Daxin Jiang, Jian Pei, Enhong Chen, ...