An association mining method for time series and its application in the stock prices of TFT-LCD industry

Chiung Fen Huang; Yen Chu Chen; An-Pin Chen

doi:10.1007/978-3-540-30185-1_13

An association mining method for time series and its application in the stock prices of TFT-LCD industry

Chiung Fen Huang, Yen Chu Chen, An-Pin Chen

Institute of Information Management

Research output: Contribution to journal › Conference article › peer-review

4 Scopus citations

Abstract

The stock price associations between the suppliers and manufacturers in the value chain of the TFT-LCD industry by means of data mining method used to improve the Apriori algorithm so that it can facilitate association mining of discrete data points in time series, is discussed. In the first phase, data are classified and preprocessed using the algorithm, then Apriori algorithm is applied to extract the strong association rules. By mining the association rules from the discrete data points in a time series, statistically significant outcomes can be obtained. Results reveal helpful information for the investors to make leveraged arbitrage profit investing decisions.

Original language	American English
Pages (from-to)	117-126
Number of pages	10
Journal	Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume	3275
DOIs	https://doi.org/10.1007/978-3-540-30185-1_13
State	Published - 2004
Event	4th Industrial Conference on Data Mining, ICDM 2004 - Advances in Data Mining: Applications in Image Mining, Medicine and Biotechnology, Management and Environmental Control, and Telecommunications - Leipzig, Germany Duration: 4 Jul 2004 → 7 Jul 2004

Keywords

Apriori Algorithm
Association rule
Data Mining
TFT-LCD
Time series analysis

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10.1007/978-3-540-30185-1_13

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title = "An association mining method for time series and its application in the stock prices of TFT-LCD industry",

abstract = "The stock price associations between the suppliers and manufacturers in the value chain of the TFT-LCD industry by means of data mining method used to improve the Apriori algorithm so that it can facilitate association mining of discrete data points in time series, is discussed. In the first phase, data are classified and preprocessed using the algorithm, then Apriori algorithm is applied to extract the strong association rules. By mining the association rules from the discrete data points in a time series, statistically significant outcomes can be obtained. Results reveal helpful information for the investors to make leveraged arbitrage profit investing decisions.",

keywords = "Apriori Algorithm, Association rule, Data Mining, TFT-LCD, Time series analysis",

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T1 - An association mining method for time series and its application in the stock prices of TFT-LCD industry

AU - Huang, Chiung Fen

AU - Chen, Yen Chu

AU - Chen, An-Pin

PY - 2004

Y1 - 2004

N2 - The stock price associations between the suppliers and manufacturers in the value chain of the TFT-LCD industry by means of data mining method used to improve the Apriori algorithm so that it can facilitate association mining of discrete data points in time series, is discussed. In the first phase, data are classified and preprocessed using the algorithm, then Apriori algorithm is applied to extract the strong association rules. By mining the association rules from the discrete data points in a time series, statistically significant outcomes can be obtained. Results reveal helpful information for the investors to make leveraged arbitrage profit investing decisions.

AB - The stock price associations between the suppliers and manufacturers in the value chain of the TFT-LCD industry by means of data mining method used to improve the Apriori algorithm so that it can facilitate association mining of discrete data points in time series, is discussed. In the first phase, data are classified and preprocessed using the algorithm, then Apriori algorithm is applied to extract the strong association rules. By mining the association rules from the discrete data points in a time series, statistically significant outcomes can be obtained. Results reveal helpful information for the investors to make leveraged arbitrage profit investing decisions.

KW - Apriori Algorithm

KW - Association rule

KW - Data Mining

KW - TFT-LCD

KW - Time series analysis

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VL - 3275

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EP - 126

JO - Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

JF - Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

T2 - 4th Industrial Conference on Data Mining, ICDM 2004 - Advances in Data Mining: Applications in Image Mining, Medicine and Biotechnology, Management and Environmental Control, and Telecommunications

Y2 - 4 July 2004 through 7 July 2004

ER -

An association mining method for time series and its application in the stock prices of TFT-LCD industry

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