Automatically Constructing Dictionaries for Extracting Meaningful Crime Information from Arabic Text

Authors:
Meshrif Alruily;Aladdin Ayesh;Hussein Zedan
Affiliations:
Software Technology Research Laboratory, De Montfort University, email:meshrif, aayesh, hzedang@dmu.ac.uk;Software Technology Research Laboratory, De Montfort University, email:meshrif, aayesh, hzedang@dmu.ac.uk;Software Technology Research Laboratory, De Montfort University, email:meshrif, aayesh, hzedang@dmu.ac.uk
Venue:
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Year:
2010

Citing 4
Cited 1

Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data

Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data
Extracting meaningful entities from police narrative reports

dg.o '02 Proceedings of the 2002 annual national conference on Digital government research
Crime Type Document Classification from Arabic Corpus

DESE '09 Proceedings of the 2009 Second International Conference on Developments in eSystems Engineering
Automatically constructing a dictionary for information extraction tasks

AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence

Crime profiling for the Arabic language using computational linguistic techniques

Information Processing and Management: an International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

Arabic is widely spoken language but very few text mining tools have been developed for Arabic language. This paper presents an algorithm for automatically building dictionaries. The target domain is crime profiling. The corpus is mined for crime type, location and nationality. This work is then validated through three experiments, the results of which show that the algorithm developed here is promising.