Daghir, Kabi (2011) Semantic Document Clustering for Crime Investigation. Masters thesis, Concordia University.
- Accepted Version
Computers are increasingly used as tools to commit crimes such as unauthorized access (hacking), drug trafficking, and child pornography. The proliferation of crimes involving
computers has created a demand for special forensic tools that allow investigators to look for evidence on a suspect’s computer by analyzing communications and data on the computer’s storage devices. Motivated by the forensic process at Sûreté du Québec (SQ), the Québec provincial police, we propose a new subject-based semantic document clustering model that allows an investigator to cluster documents stored on a suspect’s computer by grouping them into a set of overlapping clusters, each corresponding to a subject of interest initially defined by the investigator.
|Divisions:||Concordia University > Faculty of Engineering and Computer Science > Concordia Institute for Information Systems Engineering|
|Item Type:||Thesis (Masters)|
|Degree Name:||M.A. Sc.|
|Program:||Information Systems Security|
|Date:||12 September 2011|
|Thesis Supervisor(s):||Fung, Benjamin|
|Keywords:||clustering, classification, data mining, information retrieval, forensic analysis, crime investigation|
|Deposited By:||KABI DAGHIR|
|Deposited On:||17 Nov 2011 19:06|
|Last Modified:||17 Nov 2011 19:06|
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