scispace - formally typeset
Journal ArticleDOI

Ontology-based automatic summarization of web document

Junwu Zhu, +3 more
- 31 Aug 2012 - 
- Vol. 4, Iss: 14, pp 298-306
Reads0
Chats0
About
This article is published in International Journal of Advancements in Computing Technology.The article was published on 2012-08-31. It has received 5 citations till now. The article focuses on the topics: Automatic summarization & Multi-document summarization.

read more

Citations
More filters
Journal ArticleDOI

An Enhanced Latent Semantic Analysis Approach for Arabic Document Summarization

TL;DR: A new LSA-based sentence selection algorithm is proposed, in which the term description is combined with sentence description for each topic which in turn makes the generated summary more informative and diverse.
Journal ArticleDOI

An Enhanced Latent Semantic Analysis Approach for Arabic Document Summarization

TL;DR: In this article, a new LSA-based sentence selection algorithm is proposed, in which the term description is combined with sentence description for each topic which in turn makes the generated summary more informative and diverse.
Journal Article

Ontology-Based Automatic Text Summarization Using FarsNet

TL;DR: A method for summarizing Persian documents which uses ontology for recognizing the semantic relationship between different parts of a text and extracting important sentences is proposed, and the achieved results indicate the acceptable capability of the proposed method in obtaining semantic relationships available in documents and automatic text summarization.
Journal ArticleDOI

Design and Implementation of E-Commerce Recommendation System Based on Ontology Technology

TL;DR: The paper presents design and implementation of E-commerce recommendation system based on ontology technology so as to effectively improve customer satisfaction.
Journal ArticleDOI

Study on Multi-document Summarization Based on Text Segmentation

TL;DR: This paper introduces a novel approach of automatic multi-document summarization based on text segmentation by means of employing the improved DotPlotting model and establishing a sentence-based vector space model (VSM).