Text Summarization Based On Classification Using ANFIS

Jaya Kumar, Yogan and Fong , Jia Kang and Ong , Sing Goh and Khan, Atif (2017) Text Summarization Based On Classification Using ANFIS. In: Advanced Topics In Intelligent Information And Database Systems. Springer, pp. 405-417. ISBN 9783319566603

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Abstract

The information overload faced by today’s society has created a big challenge for people who want to look for relevant information from the internet.There are a lot of online documents available and digesting such large texts collection is not an easy task. Hence, automatic text summarization is required to automate the process of summarizing text by extracting only the salient information from the documents. In this paper, we propose a text summarization model based on classification using Adaptive Neuro-Fuzzy Inference System (ANFIS). The model can learn to filter high quality summary sentences. We then compare the performance of our proposed model with the existing approaches which are based on neural network and fuzzy logic techniques. ANFIS was able to alleviate the limitations in the existing approaches and the experimental finding of this study shows that the proposed model yields better results in terms of precision, recall and F-measure on the Document Understanding Conference (DUC) data corpus.

Item Type: Book Chapter
Subjects: T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Information and Communication Technology
Depositing User: Muhammad Afiz Ahmad
Date Deposited: 24 Nov 2017 09:33
Last Modified: 24 Nov 2017 09:33
URI: http://eprints.utem.edu.my/id/eprint/20040
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