Query Expansion Based on Query Log and Small World Characteristic

Authors:
Yujuan Cao;Xueping Peng;Zhao Kun;Zhendong Niu;Gx Xu;Weiqiang Wang
Affiliations:
The School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China 100081 and Beijing Command & Control Center, Beijing, China 100094;The School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China 100081;The School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China 100081;The School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China 100081 and Beijing Command & Control Center, Beijing, China 100094;The School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China 100081;The School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China 100081
Venue:
WISE '09 Proceedings of the 10th International Conference on Web Information Systems Engineering
Year:
2009

Citing 10
Cited 0

Improving the effectiveness of information retrieval with local context analysis

ACM Transactions on Information Systems (TOIS)
Probabilistic query expansion using query logs

Proceedings of the 11th international conference on World Wide Web
KeyWorld: Extracting Keywords from a Document as a Small World

DS '01 Proceedings of the 4th International Conference on Discovery Science
Optimizing web search using web click-through data

Proceedings of the thirteenth ACM international conference on Information and knowledge management
Efficient and self-tuning incremental query expansion for top-k query processing

Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Query chains: learning to rank from implicit feedback

Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Concept-based interactive query expansion

Proceedings of the 14th ACM international conference on Information and knowledge management
Generating query substitutions

Proceedings of the 15th international conference on World Wide Web
Characterizing the influence of domain expertise on web search behavior

Proceedings of the Second ACM International Conference on Web Search and Data Mining
Automatic morphological query expansion using analogy-based machine learning

ECIR'07 Proceedings of the 29th European conference on IR research

Quantified Score

Hi-index	0.00

Visualization

Abstract

Automatic query expansion is an effective way to solve the word mismatching and short query problems. This paper presents a novel approach to Expand Queries Based on User log and Small world characteristic of the document (QEBUS). When the query is submitted, the synonymic concept of the query is gotten by searching a synonymic concept dictionary. Then the query log is explored and the key words are extracted from the user clicked documents based on small world network (SWN) characteristic. By analyzing the semantic network of the document based on SWN and exploring the correlations between the key words and the queries based on mutual information, high-quality expansion terms can be gotten. The experiment results show that our technique outperforms some traditional query expansion methods significantly.