Summarizing information by means of causal sentences through causal graphs

Q1 Mathematics Journal of Applied Logic Pub Date : 2017-11-01 DOI:10.1016/j.jal.2016.11.020
C. Puente , A. Sobrino , J.A. Olivas , E. Garrido
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引用次数: 7

Abstract

The objective of this work is to propose a complete system able to extract causal sentences from a set of text documents, select the causal sentences contained, create a causal graph in base to a given concept using as source these causal sentences, and finally produce a text summary gathering all the information connected by means of this causal graph. This procedure has three main steps. The first one is focused in the extraction, filtering and selection of those causal sentences that could have relevant information for the system. The second one is focused on the composition of a suitable causal graph, removing redundant information and solving ambiguity problems. The third step is a procedure able to read the causal graph to compose a suitable answer to a proposed causal question by summarizing the information contained in it.

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通过因果图,用因果句来总结信息
本工作的目标是提出一个完整的系统,能够从一组文本文档中提取因果句,选择包含的因果句,以这些因果句为源,在基础上创建给定概念的因果图,最后生成一个文本摘要,收集通过该因果图连接的所有信息。这个过程有三个主要步骤。第一个重点是提取、过滤和选择那些可能具有系统相关信息的因果句。二是构建合适的因果图,去除冗余信息,解决歧义问题。第三步是一个程序,能够阅读因果图,通过总结其中包含的信息,为提出的因果问题组成一个合适的答案。
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来源期刊
Journal of Applied Logic
Journal of Applied Logic COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, THEORY & METHODS
CiteScore
1.13
自引率
0.00%
发文量
0
审稿时长
>12 weeks
期刊介绍: Cessation.
期刊最新文献
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