Computer Science & Information Systems Department, BITS Pilani, K K Birla Goa Campus NH 17B, Bypass, Road, Zuarinagar, Sancoale, Goa, India
 Research Article   
								
																Advancing Forensic Science: AI and Knowledge Graphs Unlock New Insights 
																Author(s): Sundararaj S. Iyengar*, Seyedsina Nabavirazavi, Hemant Rathore, Yashas Hariprasad and Naveen Kumar Chaudhary             
								
																
						 This paper introduces an AI-powered Knowledge Graph for large forensic data investigations, combining machine learning and deep learning to create a sophisticated digital investigation tool. Traditional forensic methods often suffer from a lack of synergy among experts, leading to missed insights and delayed judicial processes. Our Knowledge Graph addresses this by autonomously identifying connections between offenders or victims and analyzing crime event patterns using machine learning-based knowledge signatures and spatial cascadability metrics.
The paper details the creation of a Knowledge Graph from diverse forensic data, highlighting the challenges of data handling and standardization. It showcases the application of this approach in four real-world datasets, demonstrating its effectiveness in forensic reasoning. The results indicate that AI-enabled knowledge graphs can.. Read More»
						  
																DOI:
								10.37421/2157-7145.2024.15.615															  
Journal of Forensic Research received 2328 citations as per Google Scholar report