Crime type document classification from arabic corpus

Meshrif Alruily; Aladdin Ayesh; Hussein Zedan

doi:10.1109/DeSE.2009.50

Crime type document classification from arabic corpus

Meshrif Alruily^*, Aladdin Ayesh, Hussein Zedan

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Published conference contribution

11 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings - International Conference on Developments in eSystems Engineering, DeSE 2009
Pages	153-159
Number of pages	7
DOIs	https://doi.org/10.1109/DeSE.2009.50
Publication status	Published - 2009
Event	International Conference on Developments in eSystems Engineering, DeSE 2009 - Abu Dhabi, United Arab Emirates Duration: 14 Dec 2009 → 16 Dec 2009

Conference

Conference	International Conference on Developments in eSystems Engineering, DeSE 2009
Country/Territory	United Arab Emirates
City	Abu Dhabi
Period	14/12/09 → 16/12/09

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/DeSE.2009.50

Cite this

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title = "Crime type document classification from arabic corpus",

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.",

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AU - Zedan, Hussein

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AB - 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.

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U2 - 10.1109/DeSE.2009.50

DO - 10.1109/DeSE.2009.50

M3 - Published conference contribution

AN - SCOPUS:77949632827

SN - 9780769539126

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BT - Proceedings - International Conference on Developments in eSystems Engineering, DeSE 2009

T2 - International Conference on Developments in eSystems Engineering, DeSE 2009

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ER -

Crime type document classification from arabic corpus

Abstract

Conference

UN SDGs

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