Document Clustering and Automatic Labeling for Forensic Analysis Using High Performance Clustering Algorithm (International Journal of Engineering and Computer Science, 2015)
Forensic document the strategy for examination of different unlawful acts by computer based techniques is called as computerized scientific investigation . A huge number of records are generally inspected in computer forensic investigation. The greater part of the information in that advanced records are fundamentally unstructured. To handle or investigation of this expansive, unstructured information by inspectors is hard to be performed and drawn out. Many calculations or algorithms are applied for document clustering can encourage the revelation of new and helpful learning from the archives under examination. Clustering algorithm are key piece of this work in which number of unstructured records are given as an input and the yield is organized document position. We exhibit a methodology that applies clustering algorithm of documents to measurable examination of seized computers in examinations. One particular calculation is not a Cluster examination itself but rather the general undertaking to be explained. Different algorithms are utilized that essentially vary as a part of their idea of what they constitutes a group. We characterize the proposed methodology with K-Means algorithm and hierarchical algorithm. Likewise we can create number of clusters dynamically and cluster labeling . The execution of computer for examining a few documents is enhanced in our test approach.