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SIGIR
2009
ACM

Entropy-biased models for query representation on the click graph

13 years 10 months ago
Entropy-biased models for query representation on the click graph
Query log analysis has received substantial attention in recent years, in which the click graph is an important technique for describing the relationship between queries and URLs. State-of-the-art approaches based on the raw click frequencies for modeling the click graph, however, are not noise-eliminated. Nor do they handle heterogeneous queryURL pairs well. In this paper, we investigate and develop a novel entropy-biased framework for modeling click graphs. The intuition behind this model is that various query-URL pairs should be treated differently, i.e., common clicks on less frequent but more specific URLs are of greater value than common clicks on frequent and general URLs. Based on this intuition, we utilize the entropy information of the URLs and introduce a new concept, namely the inverse query frequency (IQF), to weigh the importance (discriminative ability) of a click on a certain URL. The IQF weighting scheme is never explicitly explored or statistically examined for any...
Hongbo Deng, Irwin King, Michael R. Lyu
Added 28 May 2010
Updated 28 May 2010
Type Conference
Year 2009
Where SIGIR
Authors Hongbo Deng, Irwin King, Michael R. Lyu
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