원문정보
보안공학연구지원센터(IJHIT)
International Journal of Hybrid Information Technology
Vol.5 No.2
2012.04
pp.207-212
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
This paper proposes a hybrid query expansion method named GAO, which derives from the fact that more and more documents have been annotated with one or several ontology concepts based on their semantic. The GAO method employs a combination of global analysis and ontology technology to improve query expansion performance. The global analysis technology is used to obtain term-concept association, and ontology technology is used to carry out semantic reasoning. Experimental results of query expansion on two different corpuses show that, compared with traditional query expansion methods, the GAO method can improve the precision effectively.
목차
Abstract
1. Introduction
2. Related Works
3. Hybrid Query Expansion Algorithm
3.1. User Query Mode
3.2. Term-concept Association Computation
4. Experiments and Results
5. Conclusion
References
1. Introduction
2. Related Works
3. Hybrid Query Expansion Algorithm
3.1. User Query Mode
3.2. Term-concept Association Computation
4. Experiments and Results
5. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보
