Rule-Based Knowledge Management in Social Threat Monitor

Abstract

Social Threat Monitor (STM) is a Web system incorporating a relational database and GIS component for enregistration of user provided data on threats. In contrast to typical Crime Mapping Systems - where only authorized services, such as Police, are allowed and responsible for selective threat reporting - in case of STM all registered citizens can input threat data of interest. Registered data can be spatially visualized allowing easy browsing of reports. Wide, distributed and unlimited access makes this kind of service a new quality on the way to threat monitoring and safety improvement. However, due to a huge volumes of complex, multi-aspect data, automated knowledge management appears indispensable. In this paper a Rule-Based System for report processing and knowledge management is proposed. A new taxonomy of rules for complex knowledge management tasks is put forward. The rules are used to assess report admissibility, access restriction, perform basic processing and threat inference. Special ECA-type rules provide immediate reaction to dangerous situations and run statistical analysis of gathered data. The rules are written in Prolog. © Springer-Verlag Berlin Heidelberg 2013.