Incremental mining with prelarge trees

Chun Wei Lin; Tzung Pei Hong; Wen Hsiang Lu; Been Chian Chien

doi:10.1007/978-3-540-69052-8_18

Incremental mining with prelarge trees

Chun Wei Lin, Tzung Pei Hong, Wen Hsiang Lu, Been Chian Chien

Department of Computer Science and Information Engineering

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

7 Citations (Scopus)

Abstract

In the past, we proposed a Fast Updated FP-tree (FUFP-tree) structure to efficiently handle new transactions and to make the tree-update process become easy. In this paper, we propose the structure of prelarge trees to incrementally mine association rules based on the concept of pre-large itemsets. Due to the properties of pre-large concepts, the proposed approach does not need to rescan the original database until a number of new transactions have been inserted. Experimental results also show that the proposed approach has a good performance for incrementally handling new transactions.

Original language	English
Title of host publication	New Frontiers in Applied Artificial Intelligence - 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008, Proceedings
Pages	169-178
Number of pages	10
DOIs	https://doi.org/10.1007/978-3-540-69052-8_18
Publication status	Published - 2008 Aug 5
Event	21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008 - Wroclaw, Poland Duration: 2008 Jun 18 → 2008 Jun 20

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5027 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008
Country/Territory	Poland
City	Wroclaw
Period	08-06-18 → 08-06-20

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-540-69052-8_18

Cite this

Lin, C. W., Hong, T. P., Lu, W. H., & Chien, B. C. (2008). Incremental mining with prelarge trees. In New Frontiers in Applied Artificial Intelligence - 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008, Proceedings (pp. 169-178). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5027 LNAI). https://doi.org/10.1007/978-3-540-69052-8_18

Lin, Chun Wei ; Hong, Tzung Pei ; Lu, Wen Hsiang et al. / Incremental mining with prelarge trees. New Frontiers in Applied Artificial Intelligence - 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008, Proceedings. 2008. pp. 169-178 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Incremental mining with prelarge trees",

abstract = "In the past, we proposed a Fast Updated FP-tree (FUFP-tree) structure to efficiently handle new transactions and to make the tree-update process become easy. In this paper, we propose the structure of prelarge trees to incrementally mine association rules based on the concept of pre-large itemsets. Due to the properties of pre-large concepts, the proposed approach does not need to rescan the original database until a number of new transactions have been inserted. Experimental results also show that the proposed approach has a good performance for incrementally handling new transactions.",

author = "Lin, {Chun Wei} and Hong, {Tzung Pei} and Lu, {Wen Hsiang} and Chien, {Been Chian}",

year = "2008",

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booktitle = "New Frontiers in Applied Artificial Intelligence - 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008, Proceedings",

note = "21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008 ; Conference date: 18-06-2008 Through 20-06-2008",

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Lin, CW, Hong, TP, Lu, WH & Chien, BC 2008, Incremental mining with prelarge trees. in New Frontiers in Applied Artificial Intelligence - 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5027 LNAI, pp. 169-178, 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008, Wroclaw, Poland, 08-06-18. https://doi.org/10.1007/978-3-540-69052-8_18

Incremental mining with prelarge trees. / Lin, Chun Wei; Hong, Tzung Pei; Lu, Wen Hsiang et al.
New Frontiers in Applied Artificial Intelligence - 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008, Proceedings. 2008. p. 169-178 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5027 LNAI).

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

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AU - Hong, Tzung Pei

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AU - Chien, Been Chian

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N2 - In the past, we proposed a Fast Updated FP-tree (FUFP-tree) structure to efficiently handle new transactions and to make the tree-update process become easy. In this paper, we propose the structure of prelarge trees to incrementally mine association rules based on the concept of pre-large itemsets. Due to the properties of pre-large concepts, the proposed approach does not need to rescan the original database until a number of new transactions have been inserted. Experimental results also show that the proposed approach has a good performance for incrementally handling new transactions.

AB - In the past, we proposed a Fast Updated FP-tree (FUFP-tree) structure to efficiently handle new transactions and to make the tree-update process become easy. In this paper, we propose the structure of prelarge trees to incrementally mine association rules based on the concept of pre-large itemsets. Due to the properties of pre-large concepts, the proposed approach does not need to rescan the original database until a number of new transactions have been inserted. Experimental results also show that the proposed approach has a good performance for incrementally handling new transactions.

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Lin CW, Hong TP, Lu WH, Chien BC. Incremental mining with prelarge trees. In New Frontiers in Applied Artificial Intelligence - 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008, Proceedings. 2008. p. 169-178. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-69052-8_18

Incremental mining with prelarge trees

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