Paper Info
Title
Extraction, Analysis And Representation Of Imperfect Conditional And Causal Sentences By Means Of A Semi-Automatic Process
Abstract
Causality is not only a matter of causal statements, but also of conditional sentences. In conditional statements, causality generally emerges from the entailment relationship between the antecedent and the consequence. This entailment is frequently vague and uncertain in nature. In this article, we present a method of retrieving crisp and imperfect conditional and causal sentences identified by some linguistic patterns. These sentences are pre-processed to obtain both single cause-effect structures and causal chains. The result is displayed automatically in an imperfect causal graph by means of a Java application. The causal graph shows the strenght of the causal link labelling it with a fuzzy quantifier and the intensity of the cause or effect nodes with linguistics hedges. The knowledge base used to provide automatic information based on causal relations was some medical texts, suited for the described process.
Year
DOI
Venue
2010
10.1109/FUZZY.2010.5584115
2010 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE 2010)
Keywords
Field
DocType
knowledge base,computational linguistics,cancer,data mining,information retrieval,linguistics,knowledge based systems,text analysis,databases,knowledge representation,artificial neural networks,java,pragmatics,causality
Knowledge representation and reasoning,Logical consequence,Causality,Conditional sentence,Imperfect,Computer science,Computational linguistics,Knowledge-based systems,Natural language processing,Artificial intelligence,Knowledge base,Machine learning
Conference
ISSN
Citations 
PageRank 
1098-7584
10
1.00
References 
Authors
7
4
Name
Order
Citations
PageRank
Cristina Puente1195.60
Alejandro Sobrino2309.59
José Angel Olivas36512.87
Roberto Merlo4111.37