Title :
A Data-Mining Approach for Input-Output Table: A Case Study of Mechanical Equipment Manufacturing Industry in China
Author :
Zhang, Ying ; Huang, Weilai ; Zhou, Quan
fDate :
Nov. 30 2009-Dec. 1 2009
Abstract :
Input-output tables provide a complete picture of the flows of products and services in the economy for a given year. Data mining is the process of analyzing data to discover patterns and relationships, which allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Based on Chinese input-output tables of Statistical Yearbook from 2000 to 2008, this paper proposes a data mining model by Using TOPSIS (technique for order preference by similarity to ideal solution) and entropy method, to analyze the industry relevancy through a case of Chinese mechanical equipment manufacturing industry. Furthermore, industrial development countermeasures and suggestions are promoted.
Keywords :
data analysis; data mining; economics; entropy; machinery production industries; production equipment; statistical analysis; Chinese input-output tables; TOPSIS; data analysis; data-mining approach; economy; entropy method; input-output table; mechanical equipment manufacturing industry; Couplings; Data analysis; Data mining; Entropy; Industrial economics; Knowledge acquisition; Knowledge management; Manufacturing industries; Mining industry; Pattern analysis; TOPSIS; data mining; entropy method; industry relevancy; mechanical equipment manufacturing industry;
Conference_Titel :
Knowledge Acquisition and Modeling, 2009. KAM '09. Second International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3888-4
