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International Workshop on Agents and Data Mining Interaction

ADMI 2013: Agents and Data Mining Interaction pp 124–135Cite as

Transitive Identity Mapping Using Force-Based Clustering

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8316))

Abstract

In most information retrieval systems, software processes (whether agent-based or not) reason about passive items of data. An alternative approach instantiates each record as an agent that actively self-organizes with other agents (including queries). Imitating the movement of bodies under physical forces, we describe a distributed algorithm (“force-based clustering,” or FBC) for dynamically clustering and querying large, heterogeneous, dynamic collections of entities. The algorithm moves entities in a virtual space in a way that estimates the transitive closure of the pairwise comparisons. We demonstrate this algorithm on a large, heterogeneous collection of records, each representing a person. We have some information about a person of interest, but no record in the collection directly matches this information. Application of FBC identifies a small subset of records that are good candidates for describing the person of interest, for further manual investigation and verification.

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Author information

Authors and Affiliations

  1. Soar Technology, 3600 Green Court, Suite 600, Ann Arbor, MI, 48105, USA

    H. Van Dyke Parunak

  2. Axon Connected, 2322 Blue Stone Hills Drive, Suite 20, Harrisonburg, VA, 22801, USA

    Sven Brueckner

Authors
  1. H. Van Dyke Parunak
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  2. Sven Brueckner
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Corresponding author

Correspondence to H. Van Dyke Parunak .

Editor information

Editors and Affiliations

  1. University of Technology Sydney, Sydney, New South Wales, Australia

    Longbing Cao

  2. Teesside University, Middlesbrough, United Kingdom

    Yifeng Zeng

  3. Aristotle University of Thessaloniki, Thessaloniki, Greece

    Andreas L. Symeonidis

  4. St. Petersburg Institute for Informatics, St. Petersburg, Russia

    Vladimir Gorodetsky

  5. Department of Informatics, Technische Universität Clausthal, Clausthal-Zellerfeld, Germany

    Jörg P. Müller

  6. University of Illinois Chicago, Chicago, Illinois, USA

    Philip S. Yu

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Van Dyke Parunak, H., Brueckner, S. (2014). Transitive Identity Mapping Using Force-Based Clustering. In: Cao, L., Zeng, Y., Symeonidis, A., Gorodetsky, V., Müller, J., Yu, P. (eds) Agents and Data Mining Interaction. ADMI 2013. Lecture Notes in Computer Science(), vol 8316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55192-5_10

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  • DOI: https://doi.org/10.1007/978-3-642-55192-5_10

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-55191-8

  • Online ISBN: 978-3-642-55192-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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