Data mining via entropy: Application on trade database

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Abdul Basit, Muhammad Saeed, Asif Ali and Zafar Iqbal

State Bank of Pakistan, Pakistan

National College of Business Administration & Economics, Pakistan

: J Comput Eng Inf Technol

Abstract

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Entropy is a mathematical tool to gather maximum information about understanding distribution, systems, surveys and databases. We are introducing entropy as a tool of data mining which provides the maximum information about the trade behavior in different regions. In this study, we also derived a new entropy measure for data mining. This study will lead us to explore the new avenues of business and investment in Pakistan. China is the biggest player of global trade from Asian region. To expand the scope of competitiveness, China is continuously investing in different projects around the world. The China–Pakistan Economic Corridor (CPEC) is one of the major projects. The corridor is considered to be an extension of China's economic ambition One Belt-One Road initiative (OBOR). In future China wants to expand her trade with the world using the CPEC to enhance the scope of competitiveness. Pakistan also believes in open trade and continuously trying to enhance trade with the world. To attain maximum advantage of CPEC, Pakistan needs to explore the opportunities for the investors and business communities. In this study, we will develop linkages between the trends of our industries, commodities and their future demand in different regions.

Biography

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Abdul Basit has completed his MS in Social Sciences at SZABIST, Pakistan. Currently, he is the PhD research scholar in the discipline of Statistics at National College of Business Administration & Economics Lahore, Pakistan. He is an Assistant Director of Statistics & DWH Department of State Bank of Pakistan. He has published four research papers in the journals and many articles were presented in national and international conferences.