Using self organizing map to cluster Arabic crime documents

Meshrif Alruily*, Aladdin Ayesh, Abdulsamad Al-Marghilani

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

16 Citations (Scopus)


This paper presents a system that combines two text mining techniques; information extraction and clustering. A rulebased 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.

Original languageEnglish
Title of host publicationProceedings of the International Multiconference on Computer Science and Information Technology, IMCSIT 2010
PublisherIEEE Computer Society
Number of pages7
ISBN (Print)9788360810279
Publication statusPublished - 2010
Externally publishedYes


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