Mining frequent closed unordered trees through natural representations

José L. Balcázar; Albert Bifet; Antoni Lozano

doi:10.1007/978-3-540-73681-3_26

Mining frequent closed unordered trees through natural representations

José L. Balcázar
, Albert Bifet
, Antoni Lozano

Universidad Politecnica de Catalunia

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collection › Contribution à une conférence › Revue par des pairs

Résumé

Many knowledge representation mechanisms consist of link-based structures; they may be studied formally by means of unordered trees. Here we consider the case where labels on the nodes are nonexistent or unreliable, and propose data mining processes focusing on just the link structure. We propose a representation of ordered trees, describe a combinatorial characterization and some properties, and use them to propose an efficient algorithm for mining frequent closed subtrees from a set of input trees. Then we focus on unordered trees, and show that intrinsic characterizations of our representation provide for a way of avoiding the repeated exploration of unordered trees, and then we give an efficient algorithm for mining frequent closed unordered trees.

langue originale	Anglais
titre	Conceptual Structures
Sous-titre	Knowledge Architectures for Smart Applications - 15th International Conference on Conceptual Structures, ICCS 2007, Proceedings
Editeur	Springer Verlag
Pages	347-359
Nombre de pages	13
ISBN (imprimé)	9783540736806
Les DOIs	https://doi.org/10.1007/978-3-540-73681-3_26
état	Publié - 1 janv. 2007
Modification externe	Oui
Evénement	15th International Conference on Conceptual Structures, ICCS 2007 - Sheffield, Royaume-Uni Durée: 22 juil. 2007 → 27 juil. 2007

Série de publications

Nom	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4604 LNAI
ISSN (imprimé)	0302-9743
ISSN (Electronique)	1611-3349

Une conférence

Une conférence	15th International Conference on Conceptual Structures, ICCS 2007
Pays/Territoire	Royaume-Uni
La ville	Sheffield
période	22/07/07 → 27/07/07

Accès au document

10.1007/978-3-540-73681-3_26

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Contient cette citation

Balcázar, J. L., Bifet, A., & Lozano, A. (2007). Mining frequent closed unordered trees through natural representations. Dans Conceptual Structures: Knowledge Architectures for Smart Applications - 15th International Conference on Conceptual Structures, ICCS 2007, Proceedings (p. 347-359). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol 4604 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-540-73681-3_26

Balcázar, José L. ; Bifet, Albert ; Lozano, Antoni. / Mining frequent closed unordered trees through natural representations. Conceptual Structures: Knowledge Architectures for Smart Applications - 15th International Conference on Conceptual Structures, ICCS 2007, Proceedings. Springer Verlag, 2007. p. 347-359 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Mining frequent closed unordered trees through natural representations",

abstract = "Many knowledge representation mechanisms consist of link-based structures; they may be studied formally by means of unordered trees. Here we consider the case where labels on the nodes are nonexistent or unreliable, and propose data mining processes focusing on just the link structure. We propose a representation of ordered trees, describe a combinatorial characterization and some properties, and use them to propose an efficient algorithm for mining frequent closed subtrees from a set of input trees. Then we focus on unordered trees, and show that intrinsic characterizations of our representation provide for a way of avoiding the repeated exploration of unordered trees, and then we give an efficient algorithm for mining frequent closed unordered trees.",

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Balcázar, JL, Bifet, A & Lozano, A 2007, Mining frequent closed unordered trees through natural representations. Dans Conceptual Structures: Knowledge Architectures for Smart Applications - 15th International Conference on Conceptual Structures, ICCS 2007, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), VOL. 4604 LNAI, Springer Verlag, p. 347-359, 15th International Conference on Conceptual Structures, ICCS 2007, Sheffield, Royaume-Uni, 22/07/07. https://doi.org/10.1007/978-3-540-73681-3_26

Mining frequent closed unordered trees through natural representations. / Balcázar, José L.; Bifet, Albert; Lozano, Antoni.
Conceptual Structures: Knowledge Architectures for Smart Applications - 15th International Conference on Conceptual Structures, ICCS 2007, Proceedings. Springer Verlag, 2007. p. 347-359 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol 4604 LNAI).

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collection › Contribution à une conférence › Revue par des pairs

TY - GEN

T1 - Mining frequent closed unordered trees through natural representations

AU - Balcázar, José L.

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PY - 2007/1/1

Y1 - 2007/1/1

N2 - Many knowledge representation mechanisms consist of link-based structures; they may be studied formally by means of unordered trees. Here we consider the case where labels on the nodes are nonexistent or unreliable, and propose data mining processes focusing on just the link structure. We propose a representation of ordered trees, describe a combinatorial characterization and some properties, and use them to propose an efficient algorithm for mining frequent closed subtrees from a set of input trees. Then we focus on unordered trees, and show that intrinsic characterizations of our representation provide for a way of avoiding the repeated exploration of unordered trees, and then we give an efficient algorithm for mining frequent closed unordered trees.

AB - Many knowledge representation mechanisms consist of link-based structures; they may be studied formally by means of unordered trees. Here we consider the case where labels on the nodes are nonexistent or unreliable, and propose data mining processes focusing on just the link structure. We propose a representation of ordered trees, describe a combinatorial characterization and some properties, and use them to propose an efficient algorithm for mining frequent closed subtrees from a set of input trees. Then we focus on unordered trees, and show that intrinsic characterizations of our representation provide for a way of avoiding the repeated exploration of unordered trees, and then we give an efficient algorithm for mining frequent closed unordered trees.

UR - https://www.scopus.com/pages/publications/37349032961

U2 - 10.1007/978-3-540-73681-3_26

DO - 10.1007/978-3-540-73681-3_26

M3 - Conference contribution

AN - SCOPUS:37349032961

SN - 9783540736806

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 347

EP - 359

BT - Conceptual Structures

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Balcázar JL, Bifet A, Lozano A. Mining frequent closed unordered trees through natural representations. Dans Conceptual Structures: Knowledge Architectures for Smart Applications - 15th International Conference on Conceptual Structures, ICCS 2007, Proceedings. Springer Verlag. 2007. p. 347-359. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-73681-3_26

Mining frequent closed unordered trees through natural representations

Résumé

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Une conférence

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Autres fichiers et liens

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