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Identifying "Best Bet" Web Search Results by Mining Past User Behavior
 

Summary: Identifying "Best Bet" Web Search Results
by Mining Past User Behavior
Eugene Agichtein
Microsoft Research
Redmond, WA, USA
eugeneag@microsoft.com
Zijian Zheng
Microsoft Corporation
Redmond, WA, USA
zijianz@microsoft.com
ABSTRACT
The top web search result is crucial for user satisfaction with the
web search experience. We argue that the importance of the
relevance at the top position necessitates special handling of the
top web search result for some queries. We propose an effective
approach of leveraging millions of past user interactions with a
web search engine to automatically detect "best bet" top results
preferred by majority of users. Interestingly, this problem can be
more effectively addressed with classification than using state-of-
the-art general ranking methods. Furthermore, we show that our

  

Source: Agichtein, Eugene - Department of Mathematics and Computer Science, Emory University

 

Collections: Computer Technologies and Information Sciences