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    題名: Text Mining Techniques and Natural Language Processing
    作者: Chen, Tzu-Chia
    日期: 2025-01-10
    上傳時間: 2025-01-17 12:05:40 (UTC+8)
    出版者: John Wiley & Sons
    摘要: Text mining is an important branch of data mining that is used to analyze the text data. Text data is any type of data like structured data, unstructured data, and semi-structured data. All types of data are collected from different sources such as multimedia applications, mobile apps, digital systems, etc. These data are beneficial to get a good insight, meaningful results. We use data mining techniques like Support Vector Machine (SVM), Random Forest (RF), Multilayer Perception (MLP), Naive Bayes (NB), etc. to analyze the hidden relationship between data. We use three kinds of data types in text mining.
    關聯: Natural Language Processing for Software Engineering, Chapter 7.
    1st edition
    DOI: 10.1002/9781394272464.ch7
    顯示於類別:[人工智慧學系] 專書之單篇

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