DocumentCode
2909991
Title
Authorship Attribution in Arabic using a hybrid of evolutionary search and linear discriminant analysis
Author
Shaker, Kareem ; Corne, David
Author_Institution
Sch. of Math. & Comput. Sci., Heriot-Watt Univ., Edinburgh, UK
fYear
2010
fDate
8-10 Sept. 2010
Firstpage
1
Lastpage
6
Abstract
Authorship Attribution is the problem of determining the authorship of one or more texts. Applications include disputed authorship, or deciding which of a collection of pieces of text were by the same author. A popular and successful approach is to characterize a specific author in terms of the usage pattern of function words. These are common words that are unrelated to subject matter, and tend to be used in specific ways by different authors. In English, a well-known collection of 70 function words is often used for this purpose. Previously, using a hybrid of evolutionary search and linear-discriminant analysis (LDA), we have shown excellent performance in authorship attribution in English based on a function word approach. Here, for the first time, we propose and test a set of Arabic function words for use in Arabic authorship attribution. Tests indicate that the chosen collection forms an effective basis for authorship attribution in Arabic.
Keywords
evolutionary computation; text analysis; Arabic authorship attribution; Arabic function word approach; evolutionary search; linear discriminant analysis; usage pattern; Accuracy; Biological cells; Books; Learning systems; Linear discriminant analysis; Support vector machine classification; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence (UKCI), 2010 UK Workshop on
Conference_Location
Colchester
Print_ISBN
978-1-4244-8774-5
Electronic_ISBN
978-1-4244-8773-8
Type
conf
DOI
10.1109/UKCI.2010.5625580
Filename
5625580
Link To Document