상세정보
학술대회
On Integrating Knowledge Graph Embedding into SPARQL Query Processing
- 발행일
- 201807
- 출처
- International Conference on Web Services (ICWS) 2018, pp.371-374
- 초록
- SPARQL is a standard query language for knowledge graphs (KGs). However, it is hard to find correct answer if KGs are incomplete or incorrect. Knowledge graph embedding (KGE) enables answering queries on such KGs by inferring unknown knowledge and removing incorrect knowledge. Hence, our long-term goal in this line of research is to propose a new framework that integrates KGE and SPARQL, which opens various research problems to be addressed. In this paper, we solve one of the most critical problems, that is, optimizing the performance of nearest neighbor (NN) search. In our evaluations, we demonstrate that the search time of state-of-the-art NN search algorithms is improved by 40% without sacrificing answer accuracy.
- KSP 제안 키워드
- Critical problems, Query Language, SPARQL query processing, Search Algorithm(GSA), Search time, knowledge graph embedding, nearest neighbor(NN), state-of-The-Art