Identification and Categorization of SMS using Deep Learning and Machine Learning Methods
Keywords:
Text message Categorization, Machine Learning, Deep Learning, Word Embedding, Contextual EmbeddingAbstract
Text messages are short messages that can be used for personal as well as professional ways to share messages without involving the internet as a mode of communication. There are some essential text messages and some are nonessential. It is crucial to filter out the nonessential messages from the essential ones. Various machine learning and deep learning methods are used to categorize the text messages. This research work uses various machine learning and deep learning methods to categorize them. To extract the features from the text messages this study uses word embedding and contextual embedding techniques. Finally, the measurement of the performances is done with the help of performance matrices and confusion matrix parameters. For the word embedding-based feature selection method the Extra Tree and LSTM are more accurate i.e. 96.86% and 98.06%. And for the sentence embedding-based feature selection method the SVM and Bi-directional LSTM are more accurate i.e. 99.1% and 99.19%.
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