Semantic association rule mining in text using domain ontology
by Ibukun Afolabi; Olaperi Sowunmi; Olawande Daramola
International Journal of Metadata, Semantics and Ontologies (IJMSO), Vol. 12, No. 1, 2017

Abstract: This paper reports a procedure for ontology-based association rule mining for knowledge extraction from text. Association rule mining (ARM) algorithms have the limitations of generating many non-interesting rules, huge number of discovered rules, and low algorithm performance. This research demonstrates a procedure for improving the performance of ARM in text mining by using domain ontology. A study context of Nigerian politics using news text from a Nigerian online newspaper was selected, and a methodology that combined natural language processing, ontology-based keywords extraction, and the modified Generating Association Rules based on Weighting (GARW) scheme was applied. The result revealed significant rule reduction in the number of generated rules, and produced rules, which are more semantically related to the problem context when compared to when ARM approaches that are not ontology-based is used. The study shows that domain ontology can improve the performance of ARM algorithms when dealing with unstructured textual data.

Online publication date: Mon, 30-Oct-2017

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 Metadata, Semantics and Ontologies (IJMSO):
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