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Blocking for Entity Resolution in the Web of Data: Challenges and Algorithms

In: Strategic Innovative Marketing

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  • Kostas Stefanidis

    (University of Tampere)

Abstract

In the Web of data, entities are described by interlinked data rather than documents on the Web. In this talk, we focus on entity resolution in the Web of data, i.e., on the problem of identifying descriptions that refer to the same real-world entity within one or across knowledge bases in the Web of data. To reduce the required number of pairwise comparisons among descriptions, methods for entity resolution typically perform a preprocessing step, called blocking, which places similar entity descriptions into blocks and executes comparisons only between descriptions within the same block. The objective of this talk is to present challenges and algorithms for blocking for entity resolution, stemming from the Web openness in describing, by an unbounded number of KBs, a multitude of entity types across domains, as well as the high heterogeneity (semantic and structural) of descriptions, even for the same types of entities.

Suggested Citation

  • Kostas Stefanidis, 2017. "Blocking for Entity Resolution in the Web of Data: Challenges and Algorithms," Springer Proceedings in Business and Economics, in: Androniki Kavoura & Damianos P. Sakas & Petros Tomaras (ed.), Strategic Innovative Marketing, pages 479-482, Springer.
    • Handle: RePEc:spr:prbchp:978-3-319-56288-9_63
    DOI: 10.1007/978-3-319-56288-9_63
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