An associative rule-based classifier for Arabic medical text
by Qasem A. Al-Radaideh; Samya S. Al-Khateeb
International Journal of Knowledge Engineering and Data Mining (IJKEDM), Vol. 3, No. 3/4, 2015

Abstract: Text classification is one of the methods used for managing, organising and retrieving the needed data among the huge available text. Several methods have been proposed to manipulate the text classification problem. In recent years, some studies proposed the use of Associative Classification (AC) approach. This paper examines an associative classification approach for the categorisation of text typed in Arabic language and related to medical domain. The approach discovers a set of association rules to build a classification model where three steps were applied to build the model: generating association rules, rule ordering and pruning, and then validation. The results of the experiments showed that the ordered decision list approach outperforms other approaches with accuracy reaching 90.6%. In general, the results of the experiments showed that association rule mining is a suitable method for building good classification models to categorise Arabic medical text.

Online publication date: Wed, 06-Jan-2016

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Knowledge Engineering and Data Mining (IJKEDM):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com