Heuristics for Connecting Heterogeneous Knowledge via FrameBase

Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9678)

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.

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Notes

Acknowledgments

The research leading to these results has received funding from the European Union Seventh Framework Programme under grant agreement No. FP7-SEC-2012-312651. Additional funding was received from National Basic Research Program of China Grants 2011CBA00300, 2011CBA00301, NSFC Grants 61033001, 61361136003, 61550110504, as well as from the Danish Council for Independent Research (DFF) under grant agreement No. DFF-4093-00301.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

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

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