Computer Science
8 years ago

New algorithm slashes computational costs for organizing massive text data!

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International Journal of Computer Applications
Time Improving Policy of Text Clustering Algorithm by Reducing Computational Overheads
Mamta Gupta, Anand Rajavat

Paper Summary

The article explores different ways to organize large amounts of text data by comparing two clustering algorithms: Modified BIRCH and K-means. The goal is to find the best method for grouping similar documents together. The researchers found that K-means is more effective at creating meaningful clusters in real-world text documents.

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