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138
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ECIR
2009
Springer
16 years 25 days ago
Classifying and Characterizing Query Intent
Understanding the intent underlying user queries may help personalize search results and improve user satisfaction. In this paper, we develop a methodology for using ad clickthroug...
Azin Ashkan, Charles L. A. Clarke, Eugene Agichtei...
140
Voted
SIGIR
2006
ACM
15 years 9 months ago
Learning user interaction models for predicting web search result preferences
Evaluating user preferences of web search results is crucial for search engine development, deployment, and maintenance. We present a real-world study of modeling the behavior of ...
Eugene Agichtein, Eric Brill, Susan T. Dumais, Rob...
110
Voted
ICCD
2002
IEEE
130views Hardware» more  ICCD 2002»
16 years 17 days ago
Branch Behavior of a Commercial OLTP Workload on Intel IA32 Processors
This paper presents a detailed branch characterization of an Oracle based commercial on-line transaction processing workload, Oracle Database Benchmark (ODB), running on an IA32 p...
Murali Annavaram, Trung A. Diep, John Paul Shen
118
Voted
SIGIR
2010
ACM
15 years 7 months ago
Predicting searcher frustration
When search engine users have trouble finding information, they may become frustrated, possibly resulting in a bad experience (even if they are ultimately successful). In a user ...
Henry A. Feild, James Allan, Rosie Jones
140
Voted
CHI
2011
ACM
14 years 7 months ago
Characterizing the usability of interactive applications through query log analysis
People routinely rely on Internet search engines to support their use of interactive systems: they issue queries to learn how to accomplish tasks, troubleshoot problems, and other...
Adam Fourney, Richard Mann, Michael Terry