An Incremental Fuzzy Approach to Finding Event Sequences

Trevor P Martin; Ben Azvine

doi:10.1007/978-3-319-40596-4_44

An Incremental Fuzzy Approach to Finding Event Sequences

Trevor P Martin, Ben Azvine

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

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Abstract

Recent years have seen increasing volumes of data generated by online systems, such as internet logs, physical access logs, transaction records, email and phone records. These contain multiple overlapping sequences of events related to different individuals and entities. Information that can be mined from these event sequences is an important re-source in understanding current behaviour, predicting future behaviour and identifying non-standard patterns and possible security breaches. Statistical machine learning approaches have had some success but do not allow human insight to be included easily. We have recently presented a framework for representing sequences of related events, with scope for assistance from human experts. This paper describes the framework and
presents a new algorithm which (i) allows the addition of new event sequences as they are identified from data or postulated by a human analyst, and (ii) allows subtraction / removal of sequences that are no longer relevant. Examination of the sequences can be used to further refine and modify general patterns of events.

Original language	English
Title of host publication	Information Processing and Management of Uncertainty in Knowledge-Based Systems
Subtitle of host publication	16th International Conference, IPMU 2016, Eindhoven, The Netherlands, June 20-24, 2016, Proceedings, Part I
Editors	Joao Paulo Carvalho, Marie-Jeanne Lesot, Uzay Kaymak, Susana Vieira, Bernadette Bouchon-Meunier, Ronald R. Yager
Publisher	Springer International Publishing AG
Pages	525-536
Number of pages	12
ISBN (Print)	978-3-319-40595-7, 978-3-319-40596-4
DOIs	https://doi.org/10.1007/978-3-319-40596-4_44
Publication status	Published - 11 Jun 2016
Event	IPMU2016 - Eindhoven, Netherlands Duration: 20 Jun 2016 → 24 Jun 2016

Publication series

Name	An Incremental Fuzzy Approach to Finding Event Sequences
Publisher	Springer International Publishing
Volume	610
ISSN (Print)	1865-0929

Conference

Conference	IPMU2016
Country/Territory	Netherlands
City	Eindhoven
Period	20/06/16 → 24/06/16

Keywords

Event Sequences
Incremental Algorithm
Fuzzy
X-mu

Access to Document

10.1007/978-3-319-40596-4_44

Trevor Martin - An Incremental Fuzzy Approach to Finding Event Sequences
This is the author accepted manuscript (AAM). The final published version (version of record) is available online via Springer at http://dx.doi.org/10.1007/978-3-319-40596-4_44. Please refer to any applicable terms of use of the publisher.
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Martin, T. P., & Azvine, B. (2016). An Incremental Fuzzy Approach to Finding Event Sequences. In J. P. Carvalho, M-J. Lesot, U. Kaymak, S. Vieira, B. Bouchon-Meunier, & R. R. Yager (Eds.), Information Processing and Management of Uncertainty in Knowledge-Based Systems: 16th International Conference, IPMU 2016, Eindhoven, The Netherlands, June 20-24, 2016, Proceedings, Part I (pp. 525-536). (An Incremental Fuzzy Approach to Finding Event Sequences; Vol. 610). Springer International Publishing AG. https://doi.org/10.1007/978-3-319-40596-4_44

Martin, Trevor P ; Azvine, Ben. / An Incremental Fuzzy Approach to Finding Event Sequences. Information Processing and Management of Uncertainty in Knowledge-Based Systems: 16th International Conference, IPMU 2016, Eindhoven, The Netherlands, June 20-24, 2016, Proceedings, Part I. editor / Joao Paulo Carvalho ; Marie-Jeanne Lesot ; Uzay Kaymak ; Susana Vieira ; Bernadette Bouchon-Meunier ; Ronald R. Yager. Springer International Publishing AG, 2016. pp. 525-536 (An Incremental Fuzzy Approach to Finding Event Sequences).

@inproceedings{1590a330a75a4586b0d03ac503c7aeb8,

title = "An Incremental Fuzzy Approach to Finding Event Sequences",

abstract = "Recent years have seen increasing volumes of data generated by online systems, such as internet logs, physical access logs, transaction records, email and phone records. These contain multiple overlapping sequences of events related to different individuals and entities. Information that can be mined from these event sequences is an important re-source in understanding current behaviour, predicting future behaviour and identifying non-standard patterns and possible security breaches. Statistical machine learning approaches have had some success but do not allow human insight to be included easily. We have recently presented a framework for representing sequences of related events, with scope for assistance from human experts. This paper describes the framework andpresents a new algorithm which (i) allows the addition of new event sequences as they are identified from data or postulated by a human analyst, and (ii) allows subtraction / removal of sequences that are no longer relevant. Examination of the sequences can be used to further refine and modify general patterns of events.",

keywords = "Event Sequences, Incremental Algorithm, Fuzzy, X-mu",

author = "Martin, {Trevor P} and Ben Azvine",

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doi = "10.1007/978-3-319-40596-4_44",

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Martin, TP & Azvine, B 2016, An Incremental Fuzzy Approach to Finding Event Sequences. in JP Carvalho, M-J Lesot, U Kaymak, S Vieira, B Bouchon-Meunier & RR Yager (eds), Information Processing and Management of Uncertainty in Knowledge-Based Systems: 16th International Conference, IPMU 2016, Eindhoven, The Netherlands, June 20-24, 2016, Proceedings, Part I. An Incremental Fuzzy Approach to Finding Event Sequences, vol. 610, Springer International Publishing AG, pp. 525-536, IPMU2016, Eindhoven, Netherlands, 20/06/16. https://doi.org/10.1007/978-3-319-40596-4_44

An Incremental Fuzzy Approach to Finding Event Sequences. / Martin, Trevor P; Azvine, Ben.

Information Processing and Management of Uncertainty in Knowledge-Based Systems: 16th International Conference, IPMU 2016, Eindhoven, The Netherlands, June 20-24, 2016, Proceedings, Part I. ed. / Joao Paulo Carvalho; Marie-Jeanne Lesot; Uzay Kaymak; Susana Vieira; Bernadette Bouchon-Meunier; Ronald R. Yager. Springer International Publishing AG, 2016. p. 525-536 (An Incremental Fuzzy Approach to Finding Event Sequences; Vol. 610).

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

TY - GEN

T1 - An Incremental Fuzzy Approach to Finding Event Sequences

AU - Martin, Trevor P

AU - Azvine, Ben

PY - 2016/6/11

Y1 - 2016/6/11

N2 - Recent years have seen increasing volumes of data generated by online systems, such as internet logs, physical access logs, transaction records, email and phone records. These contain multiple overlapping sequences of events related to different individuals and entities. Information that can be mined from these event sequences is an important re-source in understanding current behaviour, predicting future behaviour and identifying non-standard patterns and possible security breaches. Statistical machine learning approaches have had some success but do not allow human insight to be included easily. We have recently presented a framework for representing sequences of related events, with scope for assistance from human experts. This paper describes the framework andpresents a new algorithm which (i) allows the addition of new event sequences as they are identified from data or postulated by a human analyst, and (ii) allows subtraction / removal of sequences that are no longer relevant. Examination of the sequences can be used to further refine and modify general patterns of events.

AB - Recent years have seen increasing volumes of data generated by online systems, such as internet logs, physical access logs, transaction records, email and phone records. These contain multiple overlapping sequences of events related to different individuals and entities. Information that can be mined from these event sequences is an important re-source in understanding current behaviour, predicting future behaviour and identifying non-standard patterns and possible security breaches. Statistical machine learning approaches have had some success but do not allow human insight to be included easily. We have recently presented a framework for representing sequences of related events, with scope for assistance from human experts. This paper describes the framework andpresents a new algorithm which (i) allows the addition of new event sequences as they are identified from data or postulated by a human analyst, and (ii) allows subtraction / removal of sequences that are no longer relevant. Examination of the sequences can be used to further refine and modify general patterns of events.

KW - Event Sequences

KW - Incremental Algorithm

KW - Fuzzy

KW - X-mu

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DO - 10.1007/978-3-319-40596-4_44

M3 - Conference Contribution (Conference Proceeding)

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SN - 978-3-319-40596-4

T3 - An Incremental Fuzzy Approach to Finding Event Sequences

SP - 525

EP - 536

BT - Information Processing and Management of Uncertainty in Knowledge-Based Systems

A2 - Carvalho, Joao Paulo

A2 - Lesot, Marie-Jeanne

A2 - Kaymak, Uzay

A2 - Vieira, Susana

A2 - Bouchon-Meunier, Bernadette

A2 - Yager, Ronald R.

PB - Springer International Publishing AG

T2 - IPMU2016

Y2 - 20 June 2016 through 24 June 2016

ER -

Martin TP, Azvine B. An Incremental Fuzzy Approach to Finding Event Sequences. In Carvalho JP, Lesot M-J, Kaymak U, Vieira S, Bouchon-Meunier B, Yager RR, editors, Information Processing and Management of Uncertainty in Knowledge-Based Systems: 16th International Conference, IPMU 2016, Eindhoven, The Netherlands, June 20-24, 2016, Proceedings, Part I. Springer International Publishing AG. 2016. p. 525-536. (An Incremental Fuzzy Approach to Finding Event Sequences). doi: 10.1007/978-3-319-40596-4_44

An Incremental Fuzzy Approach to Finding Event Sequences

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Keywords

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