Using K-means cluster based techniques in external plagiarism detection

The primary focus is to explore the unsupervised document categorization/ clustering methods using different variations of K-means algorithm and compare it with the general N-gram based method and Vector Space Model based method.

Abstract

Text document categorization is one of the rapidly emerging research fields, where documents are identified, differentiated and classified manually or algorithmically. The paper focuses on application of automatic text document categorization in plagiarism detection domain. In today's world plagiarism has become a prime concern, especially in research and educational fields. This paper aims on the study and comparison of different methods of document categorization in external plagiarism detection. Here the primary focus is to explore the unsupervised document categorization/ clustering methods using different variations of K-means algorithm and compare it with the general N-gram based method and Vector Space Model based method. Finally the analysis and evaluation is done using data set from PAN-2013 1 and performance is compared based on precision, recall and efficiency in terms of time taken for algorithm execution.