Machine learning for text/ Charu C Aggarwal

Includes bibliography and index

Machine learning for text: an introduction -- Text preparation and similarity computation -- Matrix factorization and topic modeling -- Text clustering -- Text classification: basic models -- Linear classification and regression for text -- Classifier performance and evaluation -- Joint mining with heterogeneous data -- Information retrieval and search engines -- text sequence modeling and deep learning -- Text summarization -- Information extraction -- Opinion mining and sentiment analysis -- text segmentation and event detection

This textbook covers machine learning topics for text in detail. Since the coverage is extensive,multiple courses can be offered from the same book, depending on course level. Even though the presentation is text-centric, Chapters 3 to 7 cover machine learning algorithms that are often used indomains beyond text data. Therefore, the book can be used to offer courses not just in text analytics but also from the broader perspective of machine learning