On the Helmholtz Principle for Data Mining

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.