The similarity of web queries plays an important role in capturing frequently asked questions, most popular topics of search engine or automatic query expansion. Accurate measurement of similarity between queries is crucial. The paper presents a new model for similarity metric of web queries using user logs and applied it into information retrieval for query expansion. Different from previous works, in the new model not only word form, but also semantic information has been taken into account. Experiments show that using the new model in query expansion actually improved recall of 8.1 percent and precision of 9.2 percent, which indicates the good performance.
목차
Abstract 1. Introduction 2. Related Work 3. A New Algorithm for Similar Queries Metric 4. Queries clustering 5. Evaluation 5.1. Data set 5.2. Results analysis 6. Conclusion and Future Work References
키워드
similarity of web queriesword formsemantic informationquery expansion
저자
Lingling Meng [ Computer Science and Technology Department, Department of Educational Information Technology, East China Normal University ]
Runqing Huang [ Shanghai Municipal People's Government ]
Junzhong Gu [ Computer Science and Technology Department, East China Normal University ]
보안공학연구지원센터(IJGDC) [Science & Engineering Research Support Center, Republic of Korea(IJGDC)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Grid and Distributed Computing
간기
격월간
pISSN
2005-4262
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Grid and Distributed Computing Vol.6 No.4