Behavioural Tempo-spatial Knowledge Graph for Crime matching through Associate Questioning and Graph Theory

Conference paper

Qazi, N. and William Wong, B. L. 2017. Behavioural Tempo-spatial Knowledge Graph for Crime matching through Associate Questioning and Graph Theory. 2017 European Intelligence and Security Informatics Conference (EISIC). IEEE. https://doi.org/10.1109/EISIC.2017.29
AuthorsQazi, N. and William Wong, B. L.
TypeConference paper
Abstract

Crime matching process usually involves the time tedious and information intensive task of eliciting plausible associations among actors of crimes to identify potential suspects. Aiming towards the assistance of this procedure, we in this paper have exhibited the utilization of associative search; a relatively new search mining instrument to evoke conceivable associations from the information. We have demonstrated the use of three-dimensional, i.e. spatial, temporal, and modus operandi based similarity matching of crime pattern to establish hierarchical associations among the crime entities. Later we used these to extract plausible suspect list for an unsolved crime to facilitate the crime matching process. A knowledge graph consisting of tree structure coupled with the iconic graphic is used to visualize the plausible list. Additionally, a similarity score is calculated to rank the suspect in the plausible list. The proposed visualization aims to assist in hypothesis formulation reducing computational influence in the decision making of criminal matching process.

Year2017
Conference2017 European Intelligence and Security Informatics Conference (EISIC)
PublisherIEEE
Accepted author manuscript
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File Access Level
Anyone
Publication dates
Online28 Dec 2017
Publication process dates
Deposited08 Sep 2025
Book title2017 European Intelligence and Security Informatics Conference (EISIC)
ISBN978-1-5386-2385-5
Digital Object Identifier (DOI)https://doi.org/10.1109/EISIC.2017.29
Web address (URL) of conference proceedingshttps://ieeexplore.ieee.org/xpl/conhome/8234922/proceeding
Copyright holder© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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