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Text data clustering is a statistical and supervised machine learning algorithm for grouping text data into clusters. It is often used in text analysis, which is a branch of natural language processing (NLP) where researchers use text to identify and categorize information. The goal of text data clustering is to classify texts into clusters based on shared characteristics such as vocabulary, content, or sentiment. Text data clustering can be implemented in various NLP algorithms, such as text clustering (Naive Bayes, K-means, LDA, etc.) and machine learning
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