Ontology-based semantic search for large-scale RDF data

  • Authors:

  • Xiaolong Tang;Xin Wang;Zhiyong Feng;Longxiang Jiang

  • Affiliations:

  • School of Computer Science and Technology, Tianjin University, Tianjin, China,Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin, China;School of Computer Science and Technology, Tianjin University, Tianjin, China,Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin, China;School of Computer Science and Technology, Tianjin University, Tianjin, China,Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin, China;School of Computer Science and Technology, Tianjin University, Tianjin, China,Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin, China

  • Venue:
  • WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
  • Year:
  • 2013

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Abstract

In recent years, the Web of Data has emerged with the release of growing amount of Linked Data. Since traditional Information Retrieval (IR) technologies are no longer suit for the retrieval on Linked Data, it becomes difficult for ordinary users to retrieve the data efficiently and accurately. This paper presents a method of doing keyword search on Web of Data. We propose two distributed inverted index schemes, one of which is built from Linked Data and the other from the ontology. And as a necessary part of the ontology index, an ontology encoding scheme is also proposed. Based on the index schemes, we design an improved ranking algorithm named OntRank by introducing a semantic factor into the BM25F ranking model. The experimental evaluation illustrates the efficiency of constructing indexes and the precision of retrieval results.