Discovery of events with negative behavior against given sequential patterns

Fahad Anwar; Ilias Petrounias; Tim Morris; Vassilis Kodogiannis

doi:10.1109/IS.2010.5548370

Discovery of events with negative behavior against given sequential patterns

Fahad Anwar, Ilias Petrounias, Tim Morris, Vassilis Kodogiannis

MSM Service Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The dramatic drop in the prices of data collection and storage devices has not only enabled organisations to store almost every activity of their business processes, they can also retain every state of these activities as well. Availability of these masses of data also means that by implementing different data mining techniques we can yield more accurate and useful information to be used for important decision making. One of the key mining techniques on such data is to discover sequential patterns. Most of the existing sequential pattern mining approaches mainly deal with finding the positive behaviour of a sequential pattern that can help in predicting the next event after a sequence of events. In this paper we propose the concept of Negative Behaviour Against the Sequential Pattern (NBASP) that is to discover the events/event-sets which are unlikely to follow the given sequential pattern and discuss its applications in a variety of domains. A comprehensive problem definition and efficient algorithm to discover NBASP is presented. © 2010 IEEE.

Original language	English
Title of host publication	2010 IEEE International Conference on Intelligent Systems, IS 2010 - Proceedings\|IEEE Int. Conf. Intelligent Syst., IS - Proc.
Pages	373-378
Number of pages	5
DOIs	https://doi.org/10.1109/IS.2010.5548370 https://doi.org/10.1109/is.2010.5548370
Publication status	Published - Jul 2010
Event	2010 IEEE International Conference on Intelligent Systems, IS 2010 - London Duration: 1 Jul 2010 → …

Conference

Conference	2010 IEEE International Conference on Intelligent Systems, IS 2010
City	London
Period	1/07/10 → …

Keywords

Component
Data mining
Post mining environment
Sequential pattern

Access to Document

Cite this

@inproceedings{8a8b33dbae4242a7ae72030cad9a65f7,

title = "Discovery of events with negative behavior against given sequential patterns",

abstract = "The dramatic drop in the prices of data collection and storage devices has not only enabled organisations to store almost every activity of their business processes, they can also retain every state of these activities as well. Availability of these masses of data also means that by implementing different data mining techniques we can yield more accurate and useful information to be used for important decision making. One of the key mining techniques on such data is to discover sequential patterns. Most of the existing sequential pattern mining approaches mainly deal with finding the positive behaviour of a sequential pattern that can help in predicting the next event after a sequence of events. In this paper we propose the concept of Negative Behaviour Against the Sequential Pattern (NBASP) that is to discover the events/event-sets which are unlikely to follow the given sequential pattern and discuss its applications in a variety of domains. A comprehensive problem definition and efficient algorithm to discover NBASP is presented. {\textcopyright} 2010 IEEE.",

keywords = "Component, Data mining, Post mining environment, Sequential pattern",

author = "Fahad Anwar and Ilias Petrounias and Tim Morris and Vassilis Kodogiannis",

year = "2010",

month = jul,

doi = "10.1109/IS.2010.5548370",

language = "English",

isbn = "9781424451647",

pages = "373--378",

booktitle = "2010 IEEE International Conference on Intelligent Systems, IS 2010 - Proceedings|IEEE Int. Conf. Intelligent Syst., IS - Proc.",

note = "2010 IEEE International Conference on Intelligent Systems, IS 2010 ; Conference date: 01-07-2010",

}

Anwar, F, Petrounias, I, Morris, T & Kodogiannis, V 2010, Discovery of events with negative behavior against given sequential patterns. in 2010 IEEE International Conference on Intelligent Systems, IS 2010 - Proceedings|IEEE Int. Conf. Intelligent Syst., IS - Proc.. pp. 373-378, 2010 IEEE International Conference on Intelligent Systems, IS 2010, London, 1/07/10. https://doi.org/10.1109/IS.2010.5548370, https://doi.org/10.1109/is.2010.5548370

Discovery of events with negative behavior against given sequential patterns. / Anwar, Fahad; Petrounias, Ilias; Morris, Tim et al.
2010 IEEE International Conference on Intelligent Systems, IS 2010 - Proceedings|IEEE Int. Conf. Intelligent Syst., IS - Proc.. 2010. p. 373-378.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Discovery of events with negative behavior against given sequential patterns

AU - Anwar, Fahad

AU - Petrounias, Ilias

AU - Morris, Tim

AU - Kodogiannis, Vassilis

PY - 2010/7

Y1 - 2010/7

N2 - The dramatic drop in the prices of data collection and storage devices has not only enabled organisations to store almost every activity of their business processes, they can also retain every state of these activities as well. Availability of these masses of data also means that by implementing different data mining techniques we can yield more accurate and useful information to be used for important decision making. One of the key mining techniques on such data is to discover sequential patterns. Most of the existing sequential pattern mining approaches mainly deal with finding the positive behaviour of a sequential pattern that can help in predicting the next event after a sequence of events. In this paper we propose the concept of Negative Behaviour Against the Sequential Pattern (NBASP) that is to discover the events/event-sets which are unlikely to follow the given sequential pattern and discuss its applications in a variety of domains. A comprehensive problem definition and efficient algorithm to discover NBASP is presented. © 2010 IEEE.

AB - The dramatic drop in the prices of data collection and storage devices has not only enabled organisations to store almost every activity of their business processes, they can also retain every state of these activities as well. Availability of these masses of data also means that by implementing different data mining techniques we can yield more accurate and useful information to be used for important decision making. One of the key mining techniques on such data is to discover sequential patterns. Most of the existing sequential pattern mining approaches mainly deal with finding the positive behaviour of a sequential pattern that can help in predicting the next event after a sequence of events. In this paper we propose the concept of Negative Behaviour Against the Sequential Pattern (NBASP) that is to discover the events/event-sets which are unlikely to follow the given sequential pattern and discuss its applications in a variety of domains. A comprehensive problem definition and efficient algorithm to discover NBASP is presented. © 2010 IEEE.

KW - Component

KW - Data mining

KW - Post mining environment

KW - Sequential pattern

U2 - 10.1109/IS.2010.5548370

DO - 10.1109/IS.2010.5548370

M3 - Conference contribution

SN - 9781424451647

SP - 373

EP - 378

BT - 2010 IEEE International Conference on Intelligent Systems, IS 2010 - Proceedings|IEEE Int. Conf. Intelligent Syst., IS - Proc.

T2 - 2010 IEEE International Conference on Intelligent Systems, IS 2010

Y2 - 1 July 2010

ER -

Discovery of events with negative behavior against given sequential patterns

Abstract

Conference

Keywords

Access to Document

Fingerprint

Cite this