Paper Info
Title
A Fuzzy Approach for Sentences Relevance Assessment in Multi-document Summarization.
Abstract
Text summarization is becoming an indispensable solution for dealing with the exponential growth of textual and unstructured information in digital format. In this paper, an unsupervised method for extractive multi-document summarization is presented. This method combines the use of a semantic graph for representing textual contents and identify the most relevant topics with the processing of several sentences features applying a fuzzy logic perspective. A fuzzy aggregation operator is applied in the sentences relevance assessment process as a contribution to the multi-document summarization process. The method was evaluated with the Spanish and English texts collection of MultiLing 2015. The obtained results were measured through ROUGE metrics and compared with those obtained by other solutions reported from MultiLing2015.
Year
DOI
Venue
2019
10.1007/978-3-030-20055-8_6
14TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING MODELS IN INDUSTRIAL AND ENVIRONMENTAL APPLICATIONS (SOCO 2019)
Keywords
Field
DocType
Multi-document summarization,Extractive summarization,Semantic graph,Sentence feature,Fuzzy aggregation operator
Multi-document summarization,Automatic summarization,Graph,Computer science,Fuzzy logic,Artificial intelligence,Operator (computer programming),Natural language processing,Machine learning
Conference
Volume
ISSN
Citations 
950
2194-5357
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Eduardo Valladares-Valdés100.34
Alfredo Simón-Cuevas201.01
José A. Olivas310620.85
Francisco P. Romero423527.46