Optimum Cluster Labeling and Document Clustering for Forensic Analysis

Document clustering or unsupervised document classification is an automated process of grouping documents with similar content. Document clustering is an important task in many Information Retrieval systems. Also document clustering Algorithms can help in discovery of new and useful knowledge or novel class from the documents under analysis. This knowledge or novel class is very important issue while handling forensic analysis. Digital Forensic Investigation is the branch of scientific forensic process for investigation of material found in digital devices related to computer crimes. In computer forensics, hundreds of thousands of files per computer are examined. Hence methods for automated data analysis, such as clustering are required. Labeling large data sets with clusters bridges the effective cluster analysis to the large data set. Labeling irregular shaped clusters, distinguishing outliers and extending cluster boundary are the main problems in this stage. We address these problems and propose a cluster labeling algorithm which is very intuitive and easy to use