Analysis of Development Factors for Asian Countries using DWM on Big Data
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2017, Vol 19, Issue 2
Abstract
In today’s world, most of the developing countries are rising to become a developed country. There have been analysis of countries that experienced banking crisis in the past. However, the analysis included only data preparation process and the data mining server application for subgroup discovery induction. This paper proposes a data analytical system to perform the analysis on World Bank Indicators for Asian Countries from 1960 to 2015. The past dataset from the World Bank and other sources can be a source to predict the duration required for a country to be called a developed country. The purpose of the paper is to help the government of a nation to collect information and work on the path for the development more accurately. The analysis can be done using various methodology such as MapReduce, Canopy Clustering and Kmeans. Clustering and Reduction techniques are applied in parallel to enhance the existing technology. The outcome will be the prediction of development factors through analysis of various parameters such as Population, Gross domestic product, Trade and Employment, which affects the growth of developing countries.
Authors and Affiliations
Pallavi Varandani, Sharvari Jalit, Mrunmayee Mujumdar, Pradeep Lalwani, Prof. Arthi C I, Prof. Priya R L
Keywords
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- EP ID EP384447
- DOI 10.9790/0661-1902047882.
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