Content extraction from news web pages using tag tree
by Chandrakala Arya; Sanjay K. Dwivedi
International Journal of Autonomic Computing (IJAC), Vol. 3, No. 1, 2018

Abstract: As the web endures to develop, there is an enormous amount of information which is typically designed for its users, which makes it difficult to extract relevant data from numerous sources. In this paper, we propose an approach for extracting the main content from news web pages. Our approach is based on the concept of tokenisation of HTML page, these tokens construct the tag tree; web pages from different websites are parsed into Tag tree and generated a template from each web pages and discover matching patterns and multiple sequence alignment. It finds and removed shared token sequences from the web pages until the relevant information is extracted from them. We perform experiments on 500 web pages from ten different news websites. Experimental results show that our approach efficiently extracts the relevant information.

Online publication date: Sun, 24-Jun-2018

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 Autonomic Computing (IJAC):
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