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Conference Paper

LINDA: Distributed Web-of-Data-Scale Entity Matching

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons44151

Böhm,  Christoph
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44292

de Melo,  Gerard
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45720

Weikum,  Gerhard
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Citation

Böhm, C., de Melo, G., Naumann, F., & Weikum, G. (2012). LINDA: Distributed Web-of-Data-Scale Entity Matching. In X.-W. Chen, G. Lebanon, H. Wang, & M. J. Zaki (Eds.), CIKM'12 (pp. 2104-2108). New York, NY: ACM.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0014-5963-4
Abstract
Linked Data has emerged as a powerful way of interconnecting structured data on the Web. However, the cross-linkage between Linked Data sources is not as extensive as one would hope for. In this paper, we formalize the task of automatically creating "sameAs" links across data sources in a globally consistent manner. Our algorithm, presented in a multi-core as well as a distributed version, achieves this link generation by accounting for joint evidence of a match. Experiments confirm that our system scales beyond 100 million entities and delivers highly accurate results despite the vast heterogeneity and daunting scale.