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2011 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies
Predicting Next Search Actions with Search Engine Query Logs
Lyon France
August 22-August 27
ISBN: 978-0-7695-4513-4
Capturing users' future search actions has many potential applications such as query recommendation, web page re-ranking, advertisement arrangement, and so on. This paper predicts users' future queries and URL clicks based on their current access behaviors and global users' query logs. We explore various features from queries and clicked URLs in the users' current search sessions, select similar intents from query logs, and use them for prediction. Because of an intent shift problem in search sessions, this paper discusses which actions have more effects on the prediction, what representations are more suitable to represent users' intents, how the intent similarity is measured, and how the retrieved similar intents affect the prediction. MSN Search Query Log excerpt (RFP 2006 dataset) is taken as an experimental corpus. Three methods and the back-off models are presented.
Index Terms:
action prediction, intent mining, query logs anallysis
Citation:
Kevin Hsin-Yih Lin, Chieh-Jen Wang, Hsin-Hsi Chen, "Predicting Next Search Actions with Search Engine Query Logs," wi-iat, vol. 1, pp.227-234, 2011 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies, 2011
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