Using Self Organizing Map to cluster Arabic crime documents

This paper presents a system that combines two text mining techniques; information extraction and clustering. A rule-based approach is used to perform the information extraction task, based on the dependency relation between some intransitive verbs and prepositions. This relationship helps in extracting types of crime from documents within the crime domain. With regard to the clustering task, the Self Organizing Map (SOM) is used to cluster Arabic crime documents based on crime types. This work is then validated through experiments, the results of which show that the techniques developed here are promising.