A virtual machine for event sequence identification using fuzzy tolerance

Trevor Martin; Ben Azvine

doi:10.1109/FUZZ-IEEE.2016.7737808

A virtual machine for event sequence identification using fuzzy tolerance

Trevor Martin, Ben Azvine

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

2 Citations (Scopus)

376 Downloads (Pure)

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.

Original language	English
Title of host publication	2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2016)
Subtitle of host publication	Proceedings of a meeting held 24-29 July 2016, Vancouver, British Columbia, Canada
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	1080-1087
Number of pages	8
ISBN (Electronic)	9781509006267
ISBN (Print)	9781509006274
DOIs	https://doi.org/10.1109/FUZZ-IEEE.2016.7737808
Publication status	Published - Feb 2017

Publication series

Name	Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
ISSN (Print)	1098-7584

Keywords

Fuzzy Event Sequence Identification
Fuzzy Virtual Machine
Collaborative Intelligence

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10.1109/FUZZ-IEEE.2016.7737808

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This is the author accepted manuscript (AAM). The final published version (version of record) is available online via IEEE at http://ieeexplore.ieee.org/document/7737808/. Please refer to any applicable terms of use of the publisher.
Accepted author manuscript, 239 KB

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Professor Trevor P Martin
- Trevor.Martinbristol.acuk
- School of Engineering Mathematics and Technology - Professor of Artificial Intelligence
- Intelligent Systems Laboratory
Person: Academic , Member

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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 (pp. 1080-1087). [7737808] (Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/FUZZ-IEEE.2016.7737808

Martin, Trevor ; Azvine, Ben. / A virtual machine for event sequence identification using fuzzy tolerance. 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), 2017. pp. 1080-1087 (Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)).

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title = "A virtual machine for event sequence identification using fuzzy tolerance",

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.",

keywords = "Fuzzy Event Sequence Identification, Fuzzy Virtual Machine, Collaborative Intelligence",

author = "Trevor Martin and Ben Azvine",

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isbn = "9781509006274",

series = "Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)",

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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., 7737808, Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Institute of Electrical and Electronics Engineers (IEEE), pp. 1080-1087. https://doi.org/10.1109/FUZZ-IEEE.2016.7737808

A virtual machine for event sequence identification using fuzzy tolerance. / Martin, Trevor; Azvine, Ben.
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), 2017. p. 1080-1087 7737808 (Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)).

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

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AB - 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.

KW - Fuzzy Event Sequence Identification

KW - Fuzzy Virtual Machine

KW - Collaborative Intelligence

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DO - 10.1109/FUZZ-IEEE.2016.7737808

M3 - Conference Contribution (Conference Proceeding)

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T3 - Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

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BT - 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2016)

PB - Institute of Electrical and Electronics Engineers (IEEE)

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Martin T, Azvine B. 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). 2017. p. 1080-1087. 7737808. (Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)). Epub 2016 Nov 10. doi: 10.1109/FUZZ-IEEE.2016.7737808

A virtual machine for event sequence identification using fuzzy tolerance

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