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Multi Document Summarization Using Neuro-Fuzzy System

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Hybrid Intelligent Systems (HIS 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 734))

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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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References

  1. Patil, M.P.D.: Text summarization using fuzzy logic. Int. J. Innov. Res. Adv. Eng. 1, 42–45 (2014)

    Google Scholar 

  2. Suanmali, L., Salim, N., Binwahlan, M.S.: Fuzzy logic based method for improving text summarization. Int. J. Comput. Sci. Inf. Secur. 2, 6 (2009)

    Google Scholar 

  3. Kyoomarsi, F., Khosravi, H., Eslami, E., Dehkordy, P.K., Tajoddin, A.: Optimizing text summarization based on fuzzy logic. In: Seventh IEEE/ACIS International Conference on Computer Information Science and Optimization, pp. 347–352 (2008)

    Google Scholar 

  4. Megala, S.S.: Enriching text summarization using fuzzy logic. Int. J. Comput. Sci. Inf. Technol. 5, 863–867 (2014)

    Google Scholar 

  5. Aik, L.E.: A study of neuro-fuzzy system in approximation-based problems. Neuro Fuzzy Syst. ANFIS Adapt. Neuro Fuzzy Infer. Syst. 24, 113–130 (2008)

    Google Scholar 

  6. Nauck, D.D.: Fuzzy data analysis with NEFCLASS 2. Fuzzy Data Anal. 0: 1413–1418

    Google Scholar 

  7. Albertos, P.: Fuzzy logic controllers. Methodology. Advantages and drawbacks. In: X Congreaso Espanol Sobre Technologias Y Logica Fuzzy, pp. 1–11 (1998)

    Google Scholar 

  8. Azhari, M., Kumar, Y.J.: Improving text summarization using neuro-fuzzy approach. J. Inf. Telecommun. 0, 1–13 (2017)

    Google Scholar 

  9. Kumar, Y.J., Kang, F., Goh, O., Khan, A.: Text summarization based on classification using ANFIS. Adv. Top. Intell. (2017)

    Google Scholar 

  10. Dixit, R.S., Apte, P.S.S.: Improvement of text summarization using fuzzy logic based method. IOSR J. Comput. Eng. 5, 5–10 (2012)

    Article  Google Scholar 

  11. Sarda, A.T., Kulkarni, A.R.: Text summarization using neural networks and rhetorical structure theory. Int. J. Adv. Res. Comput. Commun. Eng. 4, 49–52 (2015)

    Google Scholar 

  12. Binwahlan, M.S., Salim, N., Suanmali, L.: Fuzzy swarm based text summarization. J. Comput. Sci. 5, 338–346 (2009)

    Article  Google Scholar 

  13. Kumar, Y.J., Salim, N., Abuobieda, A., Tawfik, A.: Multi document summarization based on news components using fuzzy cross-document relations. Appl. Soft Comput. J. 21, 265–279 (2014)

    Article  Google Scholar 

  14. Babar, S.A., Patil, P.D.: Improving performance of text summarization. In: Procedia - Procedia Computer Science, pp. 354–363. Elsevier Masson SAS (2015)

    Google Scholar 

  15. Fattah, M.A.: Probabilistic neural network based text summarization. In: Natural Language Processing and Knowledge Engineering (2008)

    Google Scholar 

  16. Lin, C., Rey, M.: ROUGE: a package for automatic evaluation of summaries. In: Proceedings of Workshop on Text Summarization of ACL, Spain (2004)

    Google Scholar 

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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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Correspondence to Yogan Jaya Kumar .

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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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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-76350-7

  • Online ISBN: 978-3-319-76351-4

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