Predicting Next Search Actions with Search Engine Query Logs

Authors:
Kevin Hsin-Yih Lin;Chieh-Jen Wang;Hsin-Hsi Chen
Affiliations:
-;-;-
Venue:
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Year:
2011

Citing 14
Cited 1

Using Association Rules to Discover Search Engines Related Queries

LA-WEB '03 Proceedings of the First Conference on Latin American Web Congress
Context-sensitive information retrieval using implicit feedback

Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Personalizing search via automated analysis of interests and activities

Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Automatic identification of user interest for personalized search

Proceedings of the 15th international conference on World Wide Web
Mining search engine query logs for query recommendation

Proceedings of the 15th international conference on World Wide Web
Improving web search ranking by incorporating user behavior information

SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
A large-scale evaluation and analysis of personalized search strategies

Proceedings of the 16th international conference on World Wide Web
The query-flow graph: model and applications

Proceedings of the 17th ACM conference on Information and knowledge management
Proceedings of the 2009 workshop on Web Search Click Data

Second ACM International Conference on Web Search and Web Data Mining
Query suggestions using query-flow graphs

Proceedings of the 2009 workshop on Web Search Click Data
Towards context-aware search by learning a very large variable length hidden markov model from search logs

Proceedings of the 18th international conference on World wide web
Beyond hyperlinks: organizing information footprints in search logs to support effective browsing

Proceedings of the 18th ACM conference on Information and knowledge management
Actively predicting diverse search intent from user browsing behaviors

Proceedings of the 19th international conference on World wide web
Context-aware ranking in web search

Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval

From machu_picchu to "rafting the urubamba river": anticipating information needs via the entity-query graph

Proceedings of the sixth ACM international conference on Web search and data mining

Quantified Score

Hi-index	0.00

Visualization

Abstract

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.