教師資料查詢 | 類別: 期刊論文 | 教師: 陳俊豪 CHUN-HAO CHEN (瀏覽個人網頁)

標題:Mining Emerging Patterns from Time Series Data with Time Gap Constraint
學年100
學期1
出版(發表)日期2011/09/01
作品名稱Mining Emerging Patterns from Time Series Data with Time Gap Constraint
作品名稱(其他語言)
著者Yu, Hsieh-Hui; Chen, Chun-Hao; Tseng, Vincent S.
單位淡江大學資訊工程學系
出版者Kumamoto: I C I C International
著錄名稱、卷期、頁數International Journal of Innovative Computing, Information and Control 7(9), pp.5515-5528
摘要Discovery of powerful contrasts between datasets is an important issue in data mining. To address this, the concept of emerging patterns (EPs) has thus been introduced by Dong and Li. EPs are a set of itemsets whose support changes significantly from one dataset to another. Although an increasing number of works focus on this topic with regard to relational databases, few have considered mining EPs in time series. In this paper, we thus propose a framework named PIPs-SAX for mining EPs from time series data. The framework contains two phases: the first phase is data transformation and the second is the EPs mining. The first phase transforms the time series data into a symbolic representation based on the SAX and PIPs algorithms. In the second phase, we propose an algorithm, called TSEPsMiner, to mine time series EPs with a time gap constraint. Experiments on financial data collected from the Taiwanese stock exchange were also made in order to evaluate the effectiveness of the proposed framework.
關鍵字Emerging patterns; Contrast sets; Time series data analysis; Symbolic aggregative approximation (SAX); Perceptually important points (PIPs)
語言英文
ISSN1349-4198
期刊性質國外
收錄於SCI
產學合作
通訊作者Tseng, Vincent S.
審稿制度
國別日本
公開徵稿
出版型式紙本
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