Role of Deep Recurrent Neural Networks in Natural Language Processing
S. T. Shenbagavalli1, D. Shanthi2, S. Naganandhini3, R. Karthikeyan4
1S. T. Shenbagavalli, Department of Computer Science and Enginnering, PSNA College of Engineering and Technology, Dindigul (Tamil Nadu), India.
2Dr. D. Shanthi, Department of Computer Science and Enginnering, PSNA College of Engineering and Technology, Dindigul (Tamil Nadu), India.
3S. Naganandhini, Department of Computer Science and Engineering and Technology, PSNA College of Engineering and Technology, Dindigul (Tamil Nadu), India.
4Dr. R. Karthikeyan, Department of Computer Science and Engineering, PSNA College of Engineering and Technology, Dindigul (Tamil Nadu), India.
Manuscript received on 21 October 2019 | Revised Manuscript received on 25 October 2019 | Manuscript Published on 02 November 2019 | PP: 4082-4084 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B15970982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1597.0982S1119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Deep learning methods are used to study hierarchical representations of data. Natural Language Processing is a group of computing methodologies used for analyzing and illustrating of Natural Language (NL). Natural Language is used to collect and present information in numerous fields. NLP can be to extract and process information in human language automatically. This paper is to highlight vital research contributions in text analysis, classification and extracting useful information using NLP.
Keywords: Deep Learning, NLP, Applications.
Scope of the Article: Deep Learning