Text mining: identification of similarity of text documents using hybrid similarity model

Author:

Prasad K. M. Shiva

Publisher

Springer Science and Business Media LLC

Subject

General Medicine

Reference38 articles.

1. Meena, Y.K., Jain, A., Gopalan, D.: Survey on the graph and cluster-based approaches in multi-document text summarization. International Conference on Recent Advances and Innovations in Engineering (ICRAIE-2014). IEEE, (2014)

2. Kallimani, J.S.: Survey on extractive text summarization methods with multi-document datasets. 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, (2018)

3. “Towards Automatic Text Summarization”, Sciforce blog spot text summarization, https://medium.com/sciforce/towards-automatic-summarization-part-2-abstractive-methods-c424386a65ea

4. Moratanch, N., Chitrakala, S.: A survey on abstractive text summarization. 2016 International Conference on Circuit, Power and Computing Technologies (ICCPCT). IEEE, (2016)

5. Yang, Z., et al.: Text dimensionality reduction with mutual information preserving mapping. Chin. J. Electron. 26(5), 919–925 (2017)

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