An intelligent RDF management system with hybrid querying approach

  • Authors:

  • Jangsu Kihm;Minho Bae;Sanggil Kang;Sangyoon Oh

  • Affiliations:

  • Department of Computer Engineering, Ajou University, Suwon, Rep. of Korea;Department of Computer Engineering, Ajou University, Suwon, Rep. of Korea;Department of Computer and Information Engineering, Inha University, Incheon, Rep. of Korea;Department of Computer Engineering, Ajou University, Suwon, Rep. of Korea

  • Venue:
  • ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part I
  • Year:
  • 2012

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Abstract

Managing a large scale RDF is a challenging problem in Semantic Web research domain since achieving efficiency and scalability is hard with keeping its intelligent level. Various approaches including indexing and keyword querying have been applied to manage RDF successfully. However, none of them address the problem from the higher level and support a massive scale RDF and a large scale user request at the same time. In this paper, we present our hybrid approach with cache and ranking to achieve efficiency, scalability, and intelligence. In our approach, a query is able to be answered quickly from the cache which holds results from the previous queries. The entity-based cache structure is designed as distributed to serve a large scale user requests. A ranking system is added to improve accuracy of returned results from the cache. We present empirical evaluations of our approach.