Categorisation of web documents using extraction ontologies
by Li Xu, David W. Embley
International Journal of Metadata, Semantics and Ontologies (IJMSO), Vol. 3, No. 1, 2008

Abstract: Automatically recognising which HTML documents on the Web contain items of interest for a user is non-trivial. As a step toward solving this problem, we propose an approach based on information-extraction ontologies. Given HTML documents, tables, and forms, our document recognition system extracts expected ontological vocabulary (keywords and keyword phrases) and expected ontological instance data (particular values for ontological concepts). We then use machine-learned rules over this extracted information to determine whether an HTML document contains items of interest. Experimental results show that our ontological approach to categorisation works well, having achieved F-measures above 90% for all applications we tried.

Online publication date: Mon, 10-Nov-2008

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