Domain Independent Framework for Automatic Text Summarization

被引：2
|
作者：
Meena, Yogesh Kumar [1 ]
Gopalani, Dinesh [1 ]
机构：
[1] Malaviya Natl Inst Technol, Jaipur 302017, Rajasthan, India
来源：
INTERNATIONAL CONFERENCE ON COMPUTER, COMMUNICATION AND CONVERGENCE (ICCC 2015) | 2015年 / 48卷
关键词：
Abstractive; Clustering; Statistical; Extractive; Summarization; Term Frequency;
D O I：
10.1016/j.procs.2015.04.207
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Due to the exponential growth of documents on internet, users want all the relevant data at one place without any hassle. This led to the growth of Automatic Text Summarization. For this purpose a number of methods have been proposed by researchers but no method is able to work on all domains of text documents. Some methods which work for News domain may fail in Medical domain to give efficient results. In this paper we proposed a domain independent framework for Automatic Text Summarization. The Process first categorises the source text and then it applies the respective category's optimal set of rules or weights or method. The major advantage of framework is that it can be applicable for both extractive and abstractive text summarization. (C) 2015 The Authors. Published by Elsevier B.V.
引用
收藏
页码：722 / 727
页数：6
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