The week's pick
Reseach Article
Assessing h- and g-Indices of Scientific Papers using k-Means Clustering
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 100 - Number 11 |
| Year of Publication: 2014 |
| Authors: S. Govinda Rao, A. Govardhan |
10.5120/17572-8266
|
S. Govinda Rao, A. Govardhan . Assessing h- and g-Indices of Scientific Papers using k-Means Clustering. International Journal of Computer Applications. 100, 11 ( August 2014), 37-41. DOI=10.5120/17572-8266
Abstract
K-means clustering technique works as a greedy algorithm for partition the n-samples into k-clusters so as to reduce the sum of the squared distances to the centroids. A very familiar task in data analysis is that of grouping a set of objects into subsets such that all elements within a group are more related among them than they are to the others. K-means clustering is a method of grouping items into k groups. In this work, an attempt has been made to study the importance of clustering techniques on h- and g-indices, which are prominent markers of scientific excellence in the fields of publishing papers in various national and international journals. From the analysis, it is evidenced that k-means clustering algorithm has successfully partitioned the set of 18 observations into 3 clusters.
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