• Vinod Sharma
• Dr. Shiv Shakti Shrivastava

Abstract:-In order to overcome the limitations, this paper proposes a research paper classification system that can cluster research papers into the meaningful class in which papers are very likely to have similar subjects. Numerous research papers have been published online as well as offline with the increasing advance of computer and information technologies, which makes it difficult for users to search and categorize their interesting research papers for a specific subject Clustering analysis method is one of the main analytical methods in data mining,the method of clustering algorithm will influence the clustering results directly. The K-means clustering algorithm is computationally faster than the other clustering algorithms. However, it produces different clustering results for different number of clusters. So, it is required to determine the number of clusters (i.e., K value) in advance before clustering.

Clustering, term frequency, centroid, inverse document frequency, unsupervised learning

"Classification of Documents using Clustering Algorithm with term frequency-inverse documents frequency", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 11, page no.a434-a443, November-2021, Available :http://www.jetir.org/papers/JETIR2111057.pdf

"Classification of Documents using Clustering Algorithm with term frequency-inverse documents frequency", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 11, page no. ppa434-a443, November-2021, Available at : http://www.jetir.org/papers/JETIR2111057.pdf