Heuristics for Connecting Heterogeneous Knowledge via FrameBase

Conference paper

DOI: 10.1007/978-3-319-34129-3_2

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9678)
Cite this paper as:
Rouces J., de Melo G., Hose K. (2016) Heuristics for Connecting Heterogeneous Knowledge via FrameBase. In: Sack H., Blomqvist E., d'Aquin M., Ghidini C., Ponzetto S., Lange C. (eds) The Semantic Web. Latest Advances and New Domains. ESWC 2016. Lecture Notes in Computer Science, vol 9678. Springer, Cham

Abstract

With recent advances in information extraction techniques, various large-scale knowledge bases covering a broad range of knowledge have become publicly available. As no single knowledge base covers all information, many applications require access to integrated knowledge from multiple knowledge bases. Achieving this, however, is challenging due to differences in knowledge representation. To address this problem, this paper proposes to use linguistic frames as a common representation and maps heterogeneous knowledge bases to the FrameBase schema, which is formed by a large inventory of these frames. We develop several methods to create complex mappings from external knowledge bases to this schema, using text similarity measures, machine learning, and different heuristics. We test them with different widely used large-scale knowledge bases, YAGO2s, Freebase and WikiData. The resulting integrated knowledge can then be queried in a homogeneous way.

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Aalborg UniversityAalborgDenmark
  2. 2.Tsinghua UniversityBeijingChina

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