New Data Structure and Algorithm for Mining Dynamic Periodic Patterns
碩士 === 靜宜大學 === 資訊管理學系研究所 === 99 === Periodic pattern mining searches useful periodic patterns in time-related datasets. Previous studies mostly concern the synchronous periodic patterns. Since static transaction database cannot provide the dynamic and timely information to obtain opportune mining r...
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ndltd-TW-099PU0053960042015-10-28T04:06:48Z http://ndltd.ncl.edu.tw/handle/34119585479660288044 New Data Structure and Algorithm for Mining Dynamic Periodic Patterns 針對動態週期性樣式探勘之新資料結構及演算法 Te-Hsun Lin 林德勳 碩士 靜宜大學 資訊管理學系研究所 99 Periodic pattern mining searches useful periodic patterns in time-related datasets. Previous studies mostly concern the synchronous periodic patterns. Since static transaction database cannot provide the dynamic and timely information to obtain opportune mining results, this study proposes the Dynamic Periodic Pattern Mining model for progressive databases. This study also presents a novel periodic pattern two-dimensional linked list structure to assemble the information of periodic patterns. For each event, the DOEOP algorithm discovers all periodic 1-patterns for all windows of interest (WOI). Finally, the DPPM algorithm can effectively generates all periodic patterns with respect to different WOIs. In this research, we test our proposed scheme and algorithm on two real datasets, Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and Dow Jones Industrial Average. The experimental results indicate that the proposed algorithm has noticeably good performance. Jieh-Shan Yeh 葉介山 2010 學位論文 ; thesis 49 zh-TW |
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碩士 === 靜宜大學 === 資訊管理學系研究所 === 99 === Periodic pattern mining searches useful periodic patterns in time-related datasets. Previous studies mostly concern the synchronous periodic patterns. Since static transaction database cannot provide the dynamic and timely information to obtain opportune mining results, this study proposes the Dynamic Periodic Pattern Mining model for progressive databases. This study also presents a novel periodic pattern two-dimensional linked list structure to assemble the information of periodic patterns. For each event, the DOEOP algorithm discovers all periodic 1-patterns for all windows of interest (WOI). Finally, the DPPM algorithm can effectively generates all periodic patterns with respect to different WOIs. In this research, we test our proposed scheme and algorithm on two real datasets, Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and Dow Jones Industrial Average. The experimental results indicate that the proposed algorithm has noticeably good performance.
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Jieh-Shan Yeh |
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Jieh-Shan Yeh Te-Hsun Lin 林德勳 |
author |
Te-Hsun Lin 林德勳 |
spellingShingle |
Te-Hsun Lin 林德勳 New Data Structure and Algorithm for Mining Dynamic Periodic Patterns |
author_sort |
Te-Hsun Lin |
title |
New Data Structure and Algorithm for Mining Dynamic Periodic Patterns |
title_short |
New Data Structure and Algorithm for Mining Dynamic Periodic Patterns |
title_full |
New Data Structure and Algorithm for Mining Dynamic Periodic Patterns |
title_fullStr |
New Data Structure and Algorithm for Mining Dynamic Periodic Patterns |
title_full_unstemmed |
New Data Structure and Algorithm for Mining Dynamic Periodic Patterns |
title_sort |
new data structure and algorithm for mining dynamic periodic patterns |
publishDate |
2010 |
url |
http://ndltd.ncl.edu.tw/handle/34119585479660288044 |
work_keys_str_mv |
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