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Publication - Professor Trevor Martin

    A virtual machine for event sequence identification using fuzzy tolerance

    Citation

    Martin, T & Azvine, B, 2017, ‘A virtual machine for event sequence identification using fuzzy tolerance’. in: 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2016): Proceedings of a meeting held 24-29 July 2016, Vancouver, British Columbia, Canada. Institute of Electrical and Electronics Engineers (IEEE), pp. 1080-1087

    Abstract

    Analysing event logs and identifying multiple overlapping sequences of events is an important task in web intelligence and in other applications involving data streams. It is ideally suited to a collaborative intelligence approach, where humans provide insight and machines perform the repetitive processing and data collection. A fuzzy approach allows flexible definition of the relations which link events into a sequence. In this paper we describe a virtual machine which enables a previously published expandable sequence pattern format to be represented as virtual machine instructions, which can filter event streams and identify fuzzily related sequences.

    Full details in the University publications repository