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Your search keyword '"Maximal Patterns"' showing total 6 results
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6 results on '"Maximal Patterns"'

1. nMITP-Miner: An Efficient Method for Mining Frequent Maximal Inter-transaction Patterns

Author

Nguyen, Thanh-Ngo, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Nguyen, Ngoc Thanh, editor, Franczyk, Bogdan, editor, Ludwig, André, editor, Núñez, Manuel, editor, Treur, Jan, editor, Vossen, Gottfried, editor, and Kozierkiewicz, Adrianna, editor

Published
2024
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2. Finding Top-N Colossal Patterns Based on Clique Search with Dynamic Update of Graph

Author

Okubo, Yoshiaki, Haraguchi, Makoto, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Domenach, Florent, editor, Ignatov, Dmitry I., editor, and Poelmans, Jonas, editor

Published
2012
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4. Modified GUIDE (LM) algorithm for mining maximal high utility patterns from data streams

Author

Chiranjeevi Manike and Hari Om

Subjects
High utility patterns, Data mining, Maximal Patterns, Anti-monotone property, Transaction projection, Electronic computers. Computer science, QA75.5-76.95
Abstract

High utility pattern mining is an emerging research topic in the data mining field. Unlike frequent pattern mining, high utility pattern mining deals with non-binary databases, in which the information about purchased quantities of items is maintained. Due to the non-existence of anti-monotone property among the utilities of itemsets, utility mining becomes a big challenge. Moreover, discovering useful patterns from the huge number of potential patterns is a mining bottleneck. However, the compact (Closed and Maximal) high utility pattern mining moderately lessens the number of patterns, but it does not solve it. Recently, an efficient framework called GUIDE, was proposed in the literature to address this issue. Though, GUIDE effectively reduced the number of high utility patterns, yet the quality of few mined patterns and their utilities are not exact. In view of this, we propose a modified MGUIDE algorithm to improve the quality and determine exact utilities of maximal patterns.

Published
2015
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6. Modified GUIDE (LM) algorithm for mining maximal high utility patterns from data streams

Author

Hari Om and Chiranjeevi Manike

Subjects
General Computer Science, Transaction projection, Property (programming), Data stream mining, Computer science, media_common.quotation_subject, computer.software_genre, lcsh:QA75.5-76.95, Bottleneck, Field (computer science), Computational Mathematics, High utility patterns, Maximal Patterns, Quality (business), Anti-monotone property, lcsh:Electronic computers. Computer science, Data mining, Algorithm, computer, Utility mining, media_common
Abstract

High utility pattern mining is an emerging research topic in the data mining field. Unlike frequent pattern mining, high utility pattern mining deals with non-binary databases, in which the information about purchased quantities of items is maintained. Due to the non-existence of anti-monotone property among the utilities of itemsets, utility mining becomes a big challenge. Moreover, discovering useful patterns from the huge number of potential patterns is a mining bottleneck. However, the compact (Closed and Maximal) high utility pattern mining moderately lessens the number of patterns, but it does not solve it. Recently, an efficient framework called GUIDE, was proposed in the literature to address this issue. Though, GUIDE effectively reduced the number of high utility patterns, yet the quality of few mined patterns and their utilities are not exact. In view of this, we propose a modified MGUIDELM algorithm to improve the quality and determine exact utilities of maximal patterns.

Published
2015
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