Text Summarization Based On Classification Using ANFIS
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 req...
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| 主要な著者: | , , , |
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| フォーマット: | Book Section |
| 言語: | English |
| 出版事項: |
Springer
2017
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| 主題: | |
| オンライン･アクセス: | http://eprints.utem.edu.my/id/eprint/20040/2/ACIIDS%202017%20-%20Published%20paper.pdf http://eprints.utem.edu.my/id/eprint/20040/ |
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| 要約: | 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. |
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