《文本分析与文本挖掘》读书笔记目录一、内容简述................................................31.1书籍简介.............................................41.2研究背景与意义.......................................4二、文本分析概述............................................62.1文本分析的定义.......................................72.2文本分析的目的与任务.................................82.3文本分析的方法与技术.................................9三、文本挖掘概述...........................................113.1文本挖掘的定义......................................123.2文本挖掘的目的与任务................................123.3文本挖掘的方法与技术................................13四、文本预处理.............................................154.1文本清洗............................................164.2文本转换............................................184.3文本特征提取........................................18五、文本特征分析...........................................205.1文本特征类型........................................215.2文本特征选择........................................225.3文本特征评估........................................24六、文本分类...............................................256.1分类算法概述........................................266.2基于规则的分类......................................276.3基于机器学习的分类..................................296.4深度学习在文本分类中的应用..........................30七、文本聚类...............................................327.1聚类算法概述........................................337.2K-均值聚类..........................................347.3层次聚类............................................35八、文本主题模型...........................................368.1主题模型概述........................................378.2LDA主题模型.........................................388.3t-SNE可视化.........................................40九、文本情感分析...........................................419.1情感分析概述........................................439.2基于规则的情感分析..................................439.3基于机器学习的情感分析..............................449.4深度学习在情感分析中的应用..........................46十、文本关联规则挖掘.......................................47十一、文本时序分析.