TY - GEN
T1 - On Integrating Knowledge Graph Embedding into SPARQL Query Processing
AU - Kang, Hyunjoong
AU - Hong, Sanghyun
AU - Lee, Kookjin
AU - Park, Noseong
AU - Kwon, Soonhyun
N1 - Funding Information:
† Corresponding author; This work was supported by the National Research Council of Science & Technology (NST) grant by the Korea government (MSIP) [No. CRC-15-05-ETRI].
Publisher Copyright:
© 2018 IEEE.
PY - 2018/9/5
Y1 - 2018/9/5
N2 - 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.
AB - 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.
KW - Knowledge Graph Embedding
KW - Nearest Neighbor Searching
KW - SPARQL Query Processing
UR - http://www.scopus.com/inward/record.url?scp=85054034214&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85054034214&partnerID=8YFLogxK
U2 - 10.1109/ICWS.2018.00064
DO - 10.1109/ICWS.2018.00064
M3 - Conference contribution
AN - SCOPUS:85054034214
SN - 9781538672471
T3 - Proceedings - 2018 IEEE International Conference on Web Services, ICWS 2018 - Part of the 2018 IEEE World Congress on Services
SP - 371
EP - 374
BT - Proceedings - 2018 IEEE International Conference on Web Services, ICWS 2018 - Part of the 2018 IEEE World Congress on Services
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 25th IEEE International Conference on Web Services, ICWS 2018
Y2 - 2 July 2018 through 7 July 2018
ER -