Title :
Crime Type Document Classification from Arabic Corpus
Author :
Alruily, Meshrif ; Ayesh, Aladdin ; Zedan, Hussein
Author_Institution :
Software Technol. Res. Lab., De Montfort Univ., Leicester, UK
Abstract :
This paper describes an initial prototype for identifying types of crime in a text within the crime domain. Two approaches are explored to perform recognition tasks. The first approach completely relies on direct recognition using gazetteers. In this case, lists of crime verbs and crime names are used. The second approach is a rule-based system. Rules are built based on the predefined crime indicator list that contains some important keywords. Even though the system is still under development, the initial results are promising.
Keywords :
classification; document handling; knowledge based systems; natural language processing; Arabic corpus; crime domain; crime indicator list; crime names; crime type document classification; crime verbs; gazetteers; recognition task; rule-based system; Data mining; Design engineering; Knowledge based systems; Laboratories; Natural language processing; Natural languages; Pattern recognition; Software prototyping; Text recognition;
Conference_Titel :
Developments in eSystems Engineering (DESE), 2009 Second International Conference on
Conference_Location :
Abu Dhabi
Print_ISBN :
978-1-4244-5401-3
Electronic_ISBN :
978-1-4244-5402-0
DOI :
10.1109/DeSE.2009.50