Presentation | 2005-05-31 Narrowing Frequent Patterns by Relation Strength in Sequencial Pattern Mining Naoki OHTSUKA, Koji IWANUMA, Hidetomo NABESHIMA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Takano at al proposed the total frequency measure that finds out all frequent sequential patterns in a single large-scale data sequence. But, this measure extracts too many frequent sequential patterns which may include noisy patterns. In this paper, we propose a method that can narrow frequent patterns with a relation strength like the mutual information between elements in a sequence. This method drastically reduces the number of frequent sequential patterns. and the ratio of remaining valid sequential patterns increased. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Data Mining / Sequential Pattern Mining / Mutual Information |
Paper # | AI2005-5 |
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Committee | AI |
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Conference Date | 2005/5/24(1days) |
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Registration To | Artificial Intelligence and Knowledge-Based Processing (AI) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Narrowing Frequent Patterns by Relation Strength in Sequencial Pattern Mining |
Sub Title (in English) | |
Keyword(1) | Data Mining |
Keyword(2) | Sequential Pattern Mining |
Keyword(3) | Mutual Information |
1st Author's Name | Naoki OHTSUKA |
1st Author's Affiliation | Computer Science and Media Engineering, Interdisciplinary, Graduate School of Medicine and Engineering, University of Yamanashi() |
2nd Author's Name | Koji IWANUMA |
2nd Author's Affiliation | Interdiscipinary Graduate School of Medicine and Engineering, University of Yamanashi |
3rd Author's Name | Hidetomo NABESHIMA |
3rd Author's Affiliation | Interdiscipinary Graduate School of Medicine and Engineering, University of Yamanashi |
Date | 2005-05-31 |
Paper # | AI2005-5 |
Volume (vol) | vol.105 |
Number (no) | 105 |
Page | pp.pp.- |
#Pages | 6 |
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