GENERATION OF A HYBRID CLUSTERING ALGORITHM FOR BIG DATA

Deepak Ahlawat, Dr.Deepali Gupta

Abstract


In this paper, a Hybrid Algorithm for clustering big data is proposed which is based on Rank Similarity. Rank Similarity is calculated by taking the sum of both Cosine and Gaussian Similarity. Proposed Technique is compared with the existing technique which is based on Cosine Similarity only. Comparison is done by taking parameters precision, recall, F-Measure, and accuracy. Results are evaluated on Java Netbeans 8.2.

Keywords


Cosine Similarity, Gaussian Similarity, Rank Similarity.

Full Text:

PDF


DOI: https://doi.org/10.26483/ijarcs.v9i1.5090

Refbacks

  • There are currently no refbacks.




Copyright (c) 2018 International Journal of Advanced Research in Computer Science