By Topic

Predicting Next Search Actions with Search Engine Query Logs

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Lin, K.H. ; Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ., Taipei, Taiwan ; Chieh-Jen Wang ; Hsin-Hsi Chen

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.

Published in:

Web Intelligence and Intelligent Agent Technology (WI-IAT), 2011 IEEE/WIC/ACM International Conference on  (Volume:1 )

Date of Conference:

22-27 Aug. 2011