Publication Type : Conference Paper
Publisher : International Conference on Contemporary Computing and Informatics
Source : International Conference on Contemporary Computing and Informatics, IEEE, Mysore (2014)
Url : http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7019659
Campus : Bengaluru
School : Department of Computer Science and Engineering, School of Engineering
Department : Computer Science
Year : 2014
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-20131 and performance is compared based on precision, recall and efficiency in terms of time taken for algorithm execution.
Cite this Research Publication : V. K and Dr. Deepa Gupta, “Using K-means Cluster based Techniques in External Plagiarism Detection”, in International Conference on Contemporary Computing and Informatics, Mysore, 2014.