Nizamani, SarwatMemon, NasrullahShah, Azhar AliNizamani, Sehrish BasirNizamani, SaadIsmaili, Imdad AliNizamani, Sehrish Basir2024-02-192024-02-192015-12-091813-1743https://hdl.handle.net/10919/118019In this paper, we present a method of crime analysis from open source information. We employed un-supervised methods of data mining to explore the facts regarding the crimes of an area of interest. The analysis is based on well known clustering and association techniques. The results show that the proposed method of crime analysis is efficient and gives a broad picture of the crimes of an area to analyst without much effort. The analysis is evaluated using manual approach, which reveals that the results produced by the proposed approach are comparable to the manual analysis, while a great amount of time is saved.Pages 677-6826 page(s)application/pdfenCrime AnalysisOpen Source InformationAssociationsClusteringInformation ExtractionUn-Supervised LearningArticle474Nizamani, Sehrish Basir [0000-0001-5419-1058]2791-0547