Mining Relevant Sequence Patterns with CP-Based Framework

Amina Kemmar; Willy Ugarte; Samir Loudni; Thierry Charnois; Yahia Lebbah; Patrice Boizumault; Bruno Cremilleux

doi:10.1109/ICTAI.2014.89

Mining Relevant Sequence Patterns with CP-Based Framework

Amina Kemmar
, Willy Ugarte
, Samir Loudni
, Thierry Charnois
, Yahia Lebbah
, Patrice Boizumault
, Bruno Cremilleux

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

14 Scopus citations

Abstract

Sequential pattern mining under various constraints is a challenging data mining task. The paper provides a generic framework based on constraint programming to discover sequence patterns defined by constraints on local patterns (e.g., Gap, regular expressions) or constraints on patterns involving combination of local patterns such as relevant subgroups and top-k patterns. This framework enables the user to mine in a declarative way both kinds of patterns. The solving step is done by exploiting the machinery of Constraint Programming. For complex patterns involving combination of local patterns, we improve the mining step by using dynamic CSP. Finally, we present two case studies in biomedical information extraction and stylistic analysis in linguistics.

Original language	English
Title of host publication	Proceedings - 2014 IEEE 26th International Conference on Tools with Artificial Intelligence, ICTAI 2014
Publisher	IEEE Computer Society
Pages	552-559
Number of pages	8
ISBN (Electronic)	9781479965724
DOIs	https://doi.org/10.1109/ICTAI.2014.89
State	Published - 12 Dec 2014
Externally published	Yes
Event	26th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2014 - Limassol, Cyprus Duration: 10 Nov 2014 → 12 Nov 2014

Publication series

Name	Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI
Volume	2014-December
ISSN (Print)	1082-3409

Conference

Conference	26th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2014
Country/Territory	Cyprus
City	Limassol
Period	10/11/14 → 12/11/14

Keywords

Constraint programming
Sequential mining
Subgroup patterns

Access to Document

10.1109/ICTAI.2014.89

Cite this

Kemmar, A., Ugarte, W., Loudni, S., Charnois, T., Lebbah, Y., Boizumault, P., & Cremilleux, B. (2014). Mining Relevant Sequence Patterns with CP-Based Framework. In Proceedings - 2014 IEEE 26th International Conference on Tools with Artificial Intelligence, ICTAI 2014 (pp. 552-559). Article 6984525 (Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI; Vol. 2014-December). IEEE Computer Society. https://doi.org/10.1109/ICTAI.2014.89

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title = "Mining Relevant Sequence Patterns with CP-Based Framework",

abstract = "Sequential pattern mining under various constraints is a challenging data mining task. The paper provides a generic framework based on constraint programming to discover sequence patterns defined by constraints on local patterns (e.g., Gap, regular expressions) or constraints on patterns involving combination of local patterns such as relevant subgroups and top-k patterns. This framework enables the user to mine in a declarative way both kinds of patterns. The solving step is done by exploiting the machinery of Constraint Programming. For complex patterns involving combination of local patterns, we improve the mining step by using dynamic CSP. Finally, we present two case studies in biomedical information extraction and stylistic analysis in linguistics.",

keywords = "Constraint programming, Sequential mining, Subgroup patterns",

author = "Amina Kemmar and Willy Ugarte and Samir Loudni and Thierry Charnois and Yahia Lebbah and Patrice Boizumault and Bruno Cremilleux",

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Kemmar, A, Ugarte, W, Loudni, S, Charnois, T, Lebbah, Y, Boizumault, P & Cremilleux, B 2014, Mining Relevant Sequence Patterns with CP-Based Framework. in Proceedings - 2014 IEEE 26th International Conference on Tools with Artificial Intelligence, ICTAI 2014., 6984525, Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI, vol. 2014-December, IEEE Computer Society, pp. 552-559, 26th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2014, Limassol, Cyprus, 10/11/14. https://doi.org/10.1109/ICTAI.2014.89

Mining Relevant Sequence Patterns with CP-Based Framework. / Kemmar, Amina; Ugarte, Willy; Loudni, Samir et al.
Proceedings - 2014 IEEE 26th International Conference on Tools with Artificial Intelligence, ICTAI 2014. IEEE Computer Society, 2014. p. 552-559 6984525 (Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI; Vol. 2014-December).

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

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AU - Boizumault, Patrice

AU - Cremilleux, Bruno

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AB - Sequential pattern mining under various constraints is a challenging data mining task. The paper provides a generic framework based on constraint programming to discover sequence patterns defined by constraints on local patterns (e.g., Gap, regular expressions) or constraints on patterns involving combination of local patterns such as relevant subgroups and top-k patterns. This framework enables the user to mine in a declarative way both kinds of patterns. The solving step is done by exploiting the machinery of Constraint Programming. For complex patterns involving combination of local patterns, we improve the mining step by using dynamic CSP. Finally, we present two case studies in biomedical information extraction and stylistic analysis in linguistics.

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KW - Sequential mining

KW - Subgroup patterns

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Kemmar A, Ugarte W, Loudni S, Charnois T, Lebbah Y, Boizumault P et al. Mining Relevant Sequence Patterns with CP-Based Framework. In Proceedings - 2014 IEEE 26th International Conference on Tools with Artificial Intelligence, ICTAI 2014. IEEE Computer Society. 2014. p. 552-559. 6984525. (Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI). doi: 10.1109/ICTAI.2014.89

Mining Relevant Sequence Patterns with CP-Based Framework

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