A semantic self-organising webpage-ranking algorithm using computational geometry across different knowledge domains
by Marios Poulos, Sozon Papavlasopoulos, V.S. Belesiotis, Nikolaos Korfiatis
International Journal of Knowledge and Web Intelligence (IJKWI), Vol. 1, No. 1/2, 2009

Abstract: In this paper we introduce a method for Web page-ranking, based on computational geometry to evaluate and test by examples, order relationships among web pages belonging to different knowledge domains. The goal is, through an organising procedure, to learn from these examples a real-valued ranking function that induces ranking via a convexity feature. We consider the problem of self-organising learning from numerical data to be represented by a well-fitted convex polygon procedure, in which the vertices correspond to descriptors representing domains of web pages. Results and statistical evaluation of procedure show that the proposed method may be characterised as accurate.

Online publication date: Wed, 19-Aug-2009

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 and Web Intelligence (IJKWI):
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