Text Mining with Machine Learning
CRC Press (Verlag)
978-1-138-60182-6 (ISBN)
The book starts with an introduction to text-based natural language data processing and its goals and problems. It focuses on machine learning, presenting various algorithms with their use and possibilities, and reviews the positives and negatives. Beginning with the initial data pre-processing, a reader can follow the steps provided in the R-language including the subsuming of various available plug-ins into the resulting software tool. A big advantage is that R also contains many libraries implementing machine learning algorithms, so a reader can concentrate on the principal target without the need to implement the details of the algorithms her- or himself. To make sense of the results, the book also provides explanations of the algorithms, which supports the final evaluation and interpretation of the results. The examples are demonstrated using realworld data from commonly accessible Internet sources.
Jan Žižka is a consultant in machine learning and data mining. He has worked as a system programmer, developer of advanced software systems, and researcher. For the last 25 years, he has devoted himself to AI and machine learning, especially text mining. He has been a faculty at a number of universities and research institutes. He has authored approximately 100 international publications. František Dařena is an associate professor and the head of the Text Mining and NLP group at the Department of Informatics, Mendel University, Brno. He has published numerous articles in international scientific journals, conference proceedings, and monographs, and is a member of editorial boards of several international journals. His research includes text/data mining, intelligent data processing, and machine learning. Arnošt Svoboda is an expert programer. His speciality includes programming languages and systems such as R, Assembler, Matlab, PL/1, Cobol, Fortran, Pascal, and others. He started as a system programmer. The last 20 years, Arnošt has worked also as a teacher and researcher at Masaryk University in Brno. His current interest are machine learning and data mining.
Introduction to the Text Mining. Problematics. Textual Data in Natural Languages and Their Computer Representation. Typical Tasks and Problems. Basic Processing Tools. Machine Learning and Its Application. Applying Sequences of Machine Learning Algorithms. R-language and Its Use for Machine Learning-Based Text Mining. Real-World-Data Examples and Their Basic Preprocessing Using R. Advanced Text Mining Using Machine Learning and R. Selecting Appropriate Machine Learning Algorithms. Examples of Typical Task Solutions. Interpretation of Results.
Erscheinungsdatum | 21.11.2019 |
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Zusatzinfo | 18 Tables, black and white; 10 Line drawings, color; 68 Line drawings, black and white; 10 Illustrations, color; 68 Illustrations, black and white |
Verlagsort | London |
Sprache | englisch |
Maße | 156 x 234 mm |
Gewicht | 485 g |
Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
Informatik ► Theorie / Studium ► Algorithmen | |
Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
ISBN-10 | 1-138-60182-9 / 1138601829 |
ISBN-13 | 978-1-138-60182-6 / 9781138601826 |
Zustand | Neuware |
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