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An Extension of the Infinite Relational Model Incorporating Interaction between Objects

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Advances in Knowledge Discovery and Data Mining (PAKDD 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7819))

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Abstract

The Infinite Relational Model (IRM) introduced by Kemp et al. (Proc. AAAI2006) is one of the well-known probabilistic generative models for the co-clustering of relational data. The IRM describes the relationship among objects based on a stochastic block structure with infinitely many clusters. Although the IRM is flexible enough to learn a hidden structure with an unknown number of clusters, it sometimes fails to detect the structure if there is a large amount of noise or outliers. To overcome this problem, in this paper we propose an extension of the IRM by introducing a subset mechanism that selects a part of the data according to the interaction among objects. We also present posterior probabilities for running collapsed Gibbs sampling to learn the model from the given data. Finally, we ran experiments on synthetic and real-world datasets, and we showed that the proposed model is superior to the IRM in an environment with noise.

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Author information

Authors and Affiliations

  1. Corporate R&D Division, Panasonic Corporation, Osaka, 571-8501, Japan

    Iku Ohama & Hiromi Iida

  2. Division of Computer Science, Hokkaido University, Hokkaido, 060-0814, Japan

    Takuya Kida & Hiroki Arimura

Authors
  1. Iku Ohama
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  2. Hiromi Iida
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  3. Takuya Kida
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  4. Hiroki Arimura
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Editor information

Editors and Affiliations

  1. School of Computing Science, Simon Fraser University, 8888 University Drive, V5A 1S6, Burnaby, BC, Canada

    Jian Pei

  2. Dept. of Computer Science and Information Engineering, Institute of Medical Informatics, National Cheng Kung University, Tainan, Taiwan

    Vincent S. Tseng

  3. Faculty of Engineering and Information Technology, University of Technology Sydney, Broadway, P.O. Box 123, 2007, Sydney, NSW, Australia

    Longbing Cao  & Guandong Xu  & 

  4. Asian Office of Aerospace Research and Development (AOARD), Air Force Office of Scientific Research (AFOSR), Air Force Research Laboratory USA, Osaka University, 7-23-17 Roppongi, 106-0032, Minato-ku, Tokyo, Japan

    Hiroshi Motoda

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Ohama, I., Iida, H., Kida, T., Arimura, H. (2013). An Extension of the Infinite Relational Model Incorporating Interaction between Objects. In: Pei, J., Tseng, V.S., Cao, L., Motoda, H., Xu, G. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2013. Lecture Notes in Computer Science(), vol 7819. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37456-2_13

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  • DOI: https://doi.org/10.1007/978-3-642-37456-2_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37455-5

  • Online ISBN: 978-3-642-37456-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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