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Local Soft Belief Updating for Relational Classification

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Foundations of Intelligent Systems (ISMIS 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4994))

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Abstract

We introduce local soft belief updating, a new heuristic for taking into account relations that exist between entities in a database. Our idea applies Pearl’s belief updating, but only in the first-order neighborhood of each node, thus avoiding any problems with loops. We apply our method to a classification problem using a subset of the Cora database of computer science articles, with Cora’s citation graph giving the relations between entities.

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Aijun An Stan Matwin Zbigniew W. Raś Dominik Ślęzak

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© 2008 Springer-Verlag Berlin Heidelberg

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Ding, G., Lax, R.F., Chen, J., Chen, P., Marx, B.D. (2008). Local Soft Belief Updating for Relational Classification. In: An, A., Matwin, S., Raś, Z.W., Ślęzak, D. (eds) Foundations of Intelligent Systems. ISMIS 2008. Lecture Notes in Computer Science(), vol 4994. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68123-6_57

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  • DOI: https://doi.org/10.1007/978-3-540-68123-6_57

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68122-9

  • Online ISBN: 978-3-540-68123-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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