Implementing Automated Reasoning in Natural Language Processing
- Authors: N. Sengottaiyan1, Rohaila Naaz2
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View Affiliations Hide Affiliations1 School of Computer Science and Engineering, JAIN (Deemed to-be University), Bangalore, India 2 College of Computing Science and Information Technology, Teerthanker Mahaveer University, Moradabad, Uttar Pradesh, India
- Source: Demystifying Emerging Trends in Machine Learning , pp 570-583
- Publication Date: February 2025
- Language: English
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One deep learning method is the Convolutional Neural Network (CNN). Natural language processing problems like text classification are simplified using this approach. In this study, we use a deep learning strategy, namely the CNN method to deal with the issue of text classification. CNNs, which require a large deal of time as well as finances to train and use, have been greatly impeded by the rise of Big Data and the increased complexity of tasks. To get around these problems, we introduce a MapReduce-based CNN that rethinks what a CNN has learned by breaking it down into a series of smaller networks and training them in parallel. Subsets of incoming text are analysed by many autonomous networks.
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