Document summarisation based on sentence ranking using vector space model
by Namita Gupta; P.C. Saxena; J.P. Gupta
International Journal of Data Mining, Modelling and Management (IJDMMM), Vol. 5, No. 4, 2013

Abstract: WWW is a repository of large collection of information available in the form of unstructured documents. Therefore, the identification of documents of interest from such a huge pool of documents is very challenging. Text summarisation technique is used in information retrieval for searching document in lesser time. Ranking of documents is made based on the summary or the abstract provided by the authors of the document which is not always possible as not all documents come with an abstract or summary. Also, when different summarisation tools are used to summarise the document, not all the topics covered within the document are reflected in its summary. In this paper, we propose a method to automate the process of text document summarisation based on the term frequency within the document at different levels - paragraph and sentence. To summarise the document, similarity between the paragraphs and sentences within the paragraph is considered using vector space model. Our proposed system evaluation on the standard reference corpus from DUC-2002 using the ROUGE package indicates comparable avg. recall, avg. precision and avg. F-measure to existing summarisation tools - Copernic, SweSum, Extractor, MSWord AutoSummariser, Intelligent, Brevity, Pertinence taking DUC-2002 (100 words) human summary as baseline summary.

Online publication date: Tue, 29-Jul-2014

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 Data Mining, Modelling and Management (IJDMMM):
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