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Comparative Analysis of Genetic k-means and Fuzzy k-modes Approach for Clustering Tweets
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 181 - Number 6 |
| Year of Publication: 2018 |
| Authors: Akash Shrivastava, M. L. Garg |
10.5120/ijca2018917461
|
Akash Shrivastava, M. L. Garg . Comparative Analysis of Genetic k-means and Fuzzy k-modes Approach for Clustering Tweets. International Journal of Computer Applications. 181, 6 ( Jul 2018), 11-14. DOI=10.5120/ijca2018917461
Abstract
Social media plays a key role in decision making process. The challenge with the social media data is that it is highly categorical in nature. The classification of dataset into some prescribed format is really a tedious task. In this paper, the existing two clustering approaches is being experimented on the twitter datasets i.e. tweets to justify the fact that clustering is really an approach essentially utilized to classify the categorical dataset. Genetic k-means and fuzzy k-modes algorithm is tested on the tweets. Results shown that genetic k-means performs better for tweets classification.
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