Abstract
This paper proposes an extraction-based hybrid model for a single text document summarization. The hybrid model is depending on the linear combination of statistical measures like sentence position, TF-IDF, aggregate similarity, centroid, and sentiment analysis. Our idea to include sentiment analysis for salient sentence extraction is derived from the concept that emotion plays an important role in communication to effectively convey any message; hence, it can play vital role in text document summarization. As we know for any sentence, emotions (calling sentiments) may be negative, positive, or neutral. Sentence which has strong sentiment are more important for us which may be either negative or positive.
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References
Luhn, H.P.: The automatic creation of literature abstracts. IBM J. Res. Dev. 2, 159–165 (1958)
Baxendale, P.B.: Machine-made index for technical literature: an experiment. IBM J. Res. Dev. 2, 354–361 (1958)
Edmundson, H.P.: New methods in automatic extracting. J. ACM 16, 264–285 (1969)
Radev, D.R., Jing, H., Stys, M., Tam, D.: Centroid-based summarization of multiple documents. Inf. Process. Manage. 40, 919–938 (2004)
Goldstein, J., Mittal, V., Carbonell, J., Callan, J.: Creating and evaluating multi-document sentence extract summaries. In: Proceedings of the 9th International Conference Information and Knowledge Management, pp. 165–172. ACM (2000)
Alguliev, R.M., Aliguliyev, R.M., Hajirahimova, M.S., Mehdiyev, C.A.: MCMR: Maximum coverage and minimum redundant text summarization model. Expert Syst. Appl. 38, 14514–14522 (2011)
Sarkar, K.: Syntactic trimming of extracted sentences for improving extractive multi document summarization. J. Comput. 2 (2010)
Carbonell, J., Goldstein, J.: The use of MMR, diversity-based reranking for reordering documents and producing summaries. In: Proceedings of the 21st International Conference Research and Development in Information Retrieval, pp. 335–336. ACM SIGIR (1998)
Lin, C.Y.: Rouge: A package for automatic evaluation of summaries. In: Proceedings of the Text Summarization Branches Out, ACL-04 Workshop, pp. 74–81 (2004)
Ko, Y., Seo, J.: An effective sentence-extraction technique using contextual information and statistical approaches for text summarization. Pattern Recogn. Lett. 29, 1366–1371 (2008)
Yeh, J.Y., Ke, H.R., Yang, W.P., Meng, I.H.: Text summarization using a trainable summarizer and latent semantic analysis. Inf. Process. Manage. 41, 75–95 (2005)
Radev, D.R., Blair-Goldensohn, S., Zhang, Z.: Experiments in single and multi-document summarization using MEAD. In: 1st Conference Document Understanding, New Orleans, LA (2001)
Kim, J.H., Kim, J.H., Hwang, D.: Korean text summarization using an aggregate similarity. In: Proceedings of the 5th International Workshop on Information Retrieval with Asian languages, pp. 111–118. ACM (2000)
Ganesan, K., Zhai, C., Han, J.: Opinosis: a graph-based approach to abstractive summarization of highly redundant opinions. In: Proceedings of the 23rd International Conference Computational Linguistics, pp. 340–348. ACL (2010)
Yadav, C.S., Sharan, A., Joshi, M.L.: Semantic graph based approach for text mining. In: International Conference Challenges in Intelligent Computing Techniques, pp. 596–601. IEEE (2014)
Yadav, C.S., Sharan, A.: Hybrid approach for single text document summarization using statistical and sentiment features. Int. J. Inf. Retr. Res. (IJIRR), 5(4), 46–70 (2015)
Acknowledgments
Thanks to UGC for funding and special thanks to Iskandar Keskes (Miracl loboratory, ANLP-Research Group, Sfax-Tunisia), Ashish Kumar (SC & SS, LAB-01, JNU).
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Yadav, C.S., Sharan, A., Kumar, R., Biswas, P. (2016). A New Approach for Single Text Document Summarization. In: Satapathy, S., Raju, K., Mandal, J., Bhateja, V. (eds) Proceedings of the Second International Conference on Computer and Communication Technologies. Advances in Intelligent Systems and Computing, vol 380. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2523-2_39
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DOI: https://doi.org/10.1007/978-81-322-2523-2_39
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