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Publication - Dr Ben Azvine

    A virtual machine for event sequence identification using fuzzy tolerance


    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


    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