K-Means Clustering for Analyzing Productivity in Light of R&D Spillover
International Journal of Information Technology, Modeling and Computing (IJITMC) Vol. 4, No.2, May 2016
10 Pages Posted: 27 Jan 2020
Date Written: 2019
The differences between countries go far beyond the physical and territorial aspects. Hence, for analytical purposes, it is essential to classify countries in groups based on some of their attributes. Investment in Research and Development (R&D) influences innovations which in turn stimulates growth of a country. In this context the productivity of the R&D expenditure is analysed pragmatically. Present study aims to discover impact of R&D expenditure on its productivity in terms of number of journal articles published, patent applications filed and trademark applications registered. A more significant analysis by means of designing prominent clusters of countries by applying unsupervised learning has been presented. In this division, percentage of Gross Domestic Product (GDP) spending on R&D and its productivity are considered.
Keywords: R&D Productivity; Data Mining; Clustering; Unsupervised Learning
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