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On the Helmholtz Principle for Data Mining

Dadachev, Boris, Balinsky, Alexander, Balinsky, Helen and Simske, Steven 2012. On the Helmholtz Principle for Data Mining. Presented at: 2012 Third International Conference on Emerging Security Technologies (EST), Lisbon, Portugal, 5-7 September 2012. Published in: Stoica, A., Zarzhitsky, D., Howells, G., Frowd, C., McDonald-Maier, K., Erdogan, A. and Arslan, T. eds. Proceedings: EST 2012: Third International Conference on Emerging Security Technologies. Los Alamitos, CA: IEEE, pp. 99-102. 10.1109/EST.2012.11

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Abstract

Unusual behaviour detection and information extraction in streams of short documents and files (emails, news, tweets, log files, messages, etc.) are important problems in security applications. In [1], [2], a new approach to rapid change detection and automatic summarization of large documents was introduced. This approach is based on a theory of social networks and ideas from image processing and especially on the Helmholtz Principle from the Gestalt Theory of human perception. In this article we modify, optimize and verify the approach from [1], [2] to unusual behaviour detection and information extraction from small documents.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Mathematics
Subjects: Q Science > QA Mathematics
Uncontrolled Keywords: Helmholtz Principle, Keywords Extraction, Small-World Networks, Summarization, Unusual Behaviour Detection
Publisher: IEEE
ISBN: 9781467324489
Last Modified: 04 Jun 2017 04:27
URI: http://orca.cf.ac.uk/id/eprint/39457

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