Machine learning books and papers

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SLCNN: Sentence-Level Convolutional Neural Network for Text Classification

Ali Jarrahi, Leila Safari , Ramin Mousa

abstract: Text classification is a fundamental task in natural language processing (NLP). Several recent studies show the success of deep learning on text processing. Convolutional neural network (CNN), as a popular deep learning model, has shown remarkable success in the task of text classification. In this paper, new baseline models have been studied for text classification using CNN. In these models, documents are fed to the network as a three-dimensional tensor representation to provide sentence-level analysis. Applying such a method enables the models to take advantage of the positional information of the sentences in the text. Besides, analysing adjacent sentences allows extracting additional features. The proposed models have been compared with the state-of-the-art models using several datasets.
Author: @Raminmousa

@Machine_learn

www.tg-me.com/us/Machine learning books and papers/com.Machine_learn/2205

6.7K viewsRamin Mousa, edited  Feb 1, 2023 at 17:10

SLCNN: Sentence-Level Convolutional Neural Network for Text Classification

Ali Jarrahi, Leila Safari , Ramin Mousa

abstract: Text classification is a fundamental task in natural language processing (NLP). Several recent studies show the success of deep learning on text processing. Convolutional neural network (CNN), as a popular deep learning model, has shown remarkable success in the task of text classification. In this paper, new baseline models have been studied for text classification using CNN. In these models, documents are fed to the network as a three-dimensional tensor representation to provide sentence-level analysis. Applying such a method enables the models to take advantage of the positional information of the sentences in the text. Besides, analysing adjacent sentences allows extracting additional features. The proposed models have been compared with the state-of-the-art models using several datasets.
Author: @Raminmousa

@Machine_learn

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