Mining Causal Relations and Concepts in Maritime Accidents Investigation Reports

Abstract

Text mining is a process of extracting information of interest, from the text. In here, we applied text mining methods to extract causal patterns from the maritime accident reports collected from the Marine Accident Investigation Branch (MAIB). These causal patterns from the accident reports provide information on various mechanisms behind accidents. These include human and organisational concepts. A careful and manual investigation of causal patterns extracted from the reports provided opportunity to collect a list of concepts present in an accident according to the investigation. In this paper we discuss the statistics of the accidents that are caused by the list of concepts that were collected in this research work and also apply Self Organising Maps for visualization.