Abstract
With the abundance of data that can be accessed quickly now, it has become one of the difficulties for people to find specific information on the web. Many documents are available and it is not easy to read each and every document. As a result, the summary of the multiple texts need to be retrieved by taking the main content or just considering parts that interest the readers most. In this paper, we propose a summary of multi document using a Neuro-Fuzzy Inference System (ANFIS). This model can be trained to identify the most salient summary sentences from the document. We evaluate our proposed model with a current methodology that relied on fuzzy logic approach using ROUGE tool. ANFIS shows better results compared to other methods on the Document Understanding Conference (DUC) corpus.
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Acknowledgements
This research work supported by Universiti Teknikal Malaysia Melaka (UTeM) and Ministry of Higher Education (MOHE), Malaysia Grant No. RAGS/1/2015/ICT02/FTMK/02/B00124.
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Azhari, M., Kumar, Y.J., Goh, O.S., Choon, N.H., Pradana, A. (2018). Multi Document Summarization Using Neuro-Fuzzy System. In: Abraham, A., Muhuri, P., Muda, A., Gandhi, N. (eds) Hybrid Intelligent Systems. HIS 2017. Advances in Intelligent Systems and Computing, vol 734. Springer, Cham. https://doi.org/10.1007/978-3-319-76351-4_23
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DOI: https://doi.org/10.1007/978-3-319-76351-4_23
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