Clustering Forensic Documents to Find Relevant Data Set |
Author(s): |
Neeraj Gadiya , G.H. RAISONI COLLEGE OF ENGINEERING AND MANAGEMENT.; Pankaj Jadhav, G.H. RAISONI COLLEGE OF ENGINEERING AND MANAGEMENT.; Vaibhav Gandhi, G.H. RAISONI COLLEGE OF ENGINEERING AND MANAGEMENT.; Rahul Thombare, G.H. RAISONI COLLEGE OF ENGINEERING AND MANAGEMENT. |
Keywords: |
Clustering Forensic, Relevant Data Set |
Abstract |
In forensic analysis, large number of data, documents and files are usually examined. Much of the data in those files consists of random data or in unstructured text, whose analysis by computer examiners is difficult to be performed and also a time consuming approach. Automated methods of analysis are very useful in such conditions. Considering this approach we can implement a system which will cluster the document set into different clusters using (K-means) and similarity measures. Algorithms that can cluster documents can prove very useful in such conditions the system will provide the forensic analyst with a clustered set of documents along with relevant set of documents from that particular cluster and that too in less time and with more accuracy. |
Other Details |
Paper ID: IJSRDV4I11196 Published in: Volume : 4, Issue : 1 Publication Date: 01/04/2016 Page(s): 1264-1265 |
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