Comprehensive log compression with frequent patterns
作者： Kimmo Hätönen , Jean François Boulicaut , Mika Klemettinen , Markus Miettinen , Cyrille Masson
DOI: 10.1007/978-3-540-45228-7_36
关键词:
摘要: In this paper we present a comprehensive log compression (CLC) method that uses frequent patterns and their condensed representations to identify repetitive information from large files generated by communications networks. We also show how the identified can be used separate filter out frequently occurring events hide other, unique or only few times events. The identification done without any prior knowledge about domain For example, no pre-defined value combinations are needed. This separation makes it easier for human observer perceive analyse amounts of data. applicability CLC is demonstrated with real-world examples data communication
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