지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- Korean Institute of Information Scientists and Engineers Journal of Computing Science and Engineering Journal of Computing Science and Engineering Vol.18 No.1
- 발행연도
- 2024.3
- 수록면
- 36 - 46 (11page)
- DOI
- 10.5626/JCSE.2024.18.1.36
이용수
초록· 키워드
오류제보하기
Current entity search models predominantly rely on term frequency and semantic similarity, often failing to fully exploit the information in the knowledge graphs. This limitation leads to the neglect of entities that could be highly relevant to the user’s query topics. To overcome these challenges and enhance entity retrieval, we introduce TRIO (Term, topic, and neural-based entity Retrieval Interpolate methOd), an entity retrieval method that employs multiple search perspectives for more relevant outcomes. TRIO stands out by seamlessly integrating three distinct search perspectives: term frequency, semantic similarity, and topic similarity. This integration is executed in a simple and effective manner, allowing TRIO to capture entities across multiple dimensions, resulting in comprehensive and accurate search results. Our experiments on the standard DBpedia-Entity V2 test collection demonstrate a substantial enhancement in the search performance of the baseline model. On average, TRIO improves NDCG and MAP performance by 12.401%, and 27.342%, respectively, compared to the best-performing baseline model.
목차
Abstract
I. INTRODUCTION
II. RELATED WORK
III. METHODOLOGY
IV. EXPERIMENTAL SETUP
V. RESULTS AND ANALYSIS
VI. DISCUSSION & FUTURE WORK
VII. CONCLUSION
REFERENCES
참고문헌 (41)
참고문헌 신청
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J. Dalton and L. Dietz, “Constructing query-specific knowledge bases,” in Proceedings of the 2013 Workshop on Automated Knowledge Base Construction (AKBC), San Francisco, CA, USA, 2013, pp. 55-0. https://doi.org/10.1145/2509558.2509568
R. Reinanda, E. Meij, and M. de Rijke, “Knowledge graphs: an information retrieval perspective,” Foundations and Trends in Information Retrieval, vol. 14, no. 4, pp. 289-444, 2020. https://doi.org/10.1561/1500000063
S. Shekarpour, A.C. Ngonga Ngomo, and S. Auer, “Question answering on interlinked data,” in Proceedings of the 22nd International Conference on World Wide Web, Rio de Janeiro, Brazil, 2013, pp. 1145-1156. https://doi.org/10.1145/2488388.2488488
J. Pound, A. K. Hudek, I. F. Ilyas, and G. Weddell, “Interpreting keyword queries over web knowledge bases,” in Proceedings of the 21st ACM International Conference on Information and Knowledge Management, Maui, HI, USA, 2012, pp. 305-314. https://doi.org/10.1145/2396761.2396803
J. Dalton and L. Dietz, “Constructing query-specific knowledge bases,” in Proceedings of the 2013 Workshop on Automated Knowledge Base Construction (AKBC), San Francisco, CA, USA, 2013, pp. 55-0. https://doi.org/10.1145/2509558.2509568
R. Reinanda, E. Meij, and M. de Rijke, “Knowledge graphs: an information retrieval perspective,” Foundations and Trends in Information Retrieval, vol. 14, no. 4, pp. 289-444, 2020. https://doi.org/10.1561/1500000063
S. Shekarpour, A.C. Ngonga Ngomo, and S. Auer, “Question answering on interlinked data,” in Proceedings of the 22nd International Conference on World Wide Web, Rio de Janeiro, Brazil, 2013, pp. 1145-1156. https://doi.org/10.1145/2488388.2488488
J. Pound, A. K. Hudek, I. F. Ilyas, and G. Weddell, “Interpreting keyword queries over web knowledge bases,” in Proceedings of the 21st ACM International Conference on Information and Knowledge Management, Maui, HI, USA, 2012, pp. 305-314. https://doi.org/10.1145/2396761.2396803
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