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2010 Third International Conference on Knowledge Discovery and Data Mining
Mining Periodic-Frequent Itemsets with Approximate Periodicity Using Interval Transaction-Ids List Tree
Phuket, Thailand
January 09-January 10
ISBN: 978-0-7695-3923-2
| ASCII Text | x | ||
| Komate Amphawan, Athasit Surarerks, Philippe Lenca, "Mining Periodic-Frequent Itemsets with Approximate Periodicity Using Interval Transaction-Ids List Tree," International Workshop on Knowledge Discovery and Data Mining, pp. 245-248, 2010 Third International Conference on Knowledge Discovery and Data Mining, 2010. | |||
| BibTex | x | ||
| @article{ 10.1109/WKDD.2010.126, author = {Komate Amphawan and Athasit Surarerks and Philippe Lenca}, title = {Mining Periodic-Frequent Itemsets with Approximate Periodicity Using Interval Transaction-Ids List Tree}, journal ={International Workshop on Knowledge Discovery and Data Mining}, volume = {0}, year = {2010}, isbn = {978-0-7695-3923-2}, pages = {245-248}, doi = {http://doi.ieeecomputersociety.org/10.1109/WKDD.2010.126}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - International Workshop on Knowledge Discovery and Data Mining TI - Mining Periodic-Frequent Itemsets with Approximate Periodicity Using Interval Transaction-Ids List Tree SN - 978-0-7695-3923-2 SP245 EP248 A1 - Komate Amphawan, A1 - Athasit Surarerks, A1 - Philippe Lenca, PY - 2010 KW - Data mining KW - knowledge discovery KW - frequent itemsets KW - periodic-frequent itemsets VL - 0 JA - International Workshop on Knowledge Discovery and Data Mining ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/WKDD.2010.126
Temporal periodicity of itemset appearance can be regarded as an important criterion for measuring the interestingness of itemsets in several application. A frequent itemset can be said periodic-frequent in a database if it appears at a regular interval given by the user. In this paper, we propose a concept of the approximate periodicity of each itemset. Moreover, a new tree-based data structure, called ITL-tree (Interval Transaction-ids List tree), is proposed. Our tree structure maintains an approximation of the occurrence information in a highly compact manner for the periodic-frequent itemsets mining. A pattern-growth mining is used to generate all of periodic-frequent itemsets by a bottom-up traversal of the ITL-tree for user-given periodicity and support thresholds. The performance study shows that our data structure is very efficient for mining periodic-frequent itemsets with approximate periodicity results.
Index Terms:
Data mining, knowledge discovery, frequent itemsets, periodic-frequent itemsets
Citation:
Komate Amphawan, Athasit Surarerks, Philippe Lenca, "Mining Periodic-Frequent Itemsets with Approximate Periodicity Using Interval Transaction-Ids List Tree," wkdd, pp.245-248, 2010 Third International Conference on Knowledge Discovery and Data Mining, 2010
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