Earticle

초록

영어

Query expansion (QE) is one of the key technologies to improve retrieval efficiency. Many studies on query expansion with relationships from single local corpus suffer from two problems resulting in low retrieval performance: term relationships are limited and unlisted query terms have no expansion terms. To address these problems, relationships between terms captured from Wikipedia are superimposed to the basic Markov network that pre-built using single local corpus. A new larger Markov network is formed with more and richer relationship for each term. Evaluation is performed on three standard information retrieval corpuses including ADI, CISI and CACM.Experimental results show that the proposed technique of superimposed Markov network is effective to select more and confident candidatesfor query expansion and it outperforms other state-of-the-art QE methods.

목차

Abstract
 1. Introduction
 2. Related Work
  2.1 Query Expansion
  2.2 Markov Network Model
 3. TheThree-step Constructionof Markov Network
  3.1 Construction of B-Markov Network
  3.2 Constructionof W-Markov Network
  3.3 Superimposition to C-Markov Network
 4. Experiment Validation
  4.1 Experimental Setup
  4.2 Experimental Results
 5. Conclusion
 References

키워드

저자

• Lixin Gan [ School of Math and Computer Science,JiangxiScience &Technology Normal University,Nanchang, China ]
• Huan Hong [ School of Computer Information Engineering,Jiangxi Normal University,Nanchang, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605