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Improved Approach to Extract Knowledge from Unstructured Data Using Applied Natural Language Processing Techniques

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1090))

Abstract

Extraction of meaningful knowledge from a unstructured data is a complex task. In the literature, efforts have been made using text mining approaches. These approaches employ rich amount of resources in mining the textual datasets. In this paper, we focus on optimization of mining algorithm of text data to generate the automatic text summarization. In this approach, we extract text summaries from the text data carpus using natural language processing techniques. We propose a mining approach in semantic parsing and generate the automatic text summaries. We conduct the experiments on the real-world dataset and show the proposed approach is useful than the existing approaches.

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Correspondence to U. Mahender .

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Mahender, U., Kumara Swamy, M., Shaik, H., Kumar, S. (2020). Improved Approach to Extract Knowledge from Unstructured Data Using Applied Natural Language Processing Techniques. In: Raju, K., Govardhan, A., Rani, B., Sridevi, R., Murty, M. (eds) Proceedings of the Third International Conference on Computational Intelligence and Informatics . Advances in Intelligent Systems and Computing, vol 1090. Springer, Singapore. https://doi.org/10.1007/978-981-15-1480-7_12

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