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:Fuzzy data mining for time-series data
學年100
學期1
出版(發表)日期2012/01/01
作品名稱Fuzzy data mining for time-series data
作品名稱(其他語言)
著者Chen, Chun-Hao; Hong, Tzung-Pei; Tseng, Vincent S.
單位淡江大學資訊工程學系
出版者Amsterdam: Elsevier BV
著錄名稱、卷期、頁數Applied Soft Computing 12(1), pp.536–542
摘要Time series analysis has always been an important and interesting research field due to its frequent appearance in different applications. In the past, many approaches based on regression, neural networks and other mathematical models were proposed to analyze the time series. In this paper, we attempt to use the data mining technique to analyze time series. Many previous studies on data mining have focused on handling binary-valued data. Time series data, however, are usually quantitative values. We thus extend our previous fuzzy mining approach for handling time-series data to find linguistic association rules. The proposed approach first uses a sliding window to generate continues subsequences from a given time series and then analyzes the fuzzy itemsets from these subsequences. Appropriate post-processing is then performed to remove redundant patterns. Experiments are also made to show the performance of the proposed mining algorithm. Since the final results are represented by linguistic rules, they will be friendlier to human than quantitative representation.
關鍵字Association rule; Data mining; Fuzzy set; Sliding window; Time series
語言英文
ISSN1568-4946
期刊性質國外
收錄於SCI
產學合作
通訊作者Hong, Tzung-Pei
審稿制度
國別荷蘭
公開徵稿
出版型式紙本
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