Text Mining: Applications and Theory
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This volume demonstrates how advancements in the fields of applied mathematics, computer science, machine learning, and natural language processing can collectively capture, classify, and interpret words and their contexts. As suggested in the preface, text mining is needed when “words are not enough.”
- Provides state-of-the-art algorithms and techniques for critical tasks in text mining applications, such as clustering, classification, anomaly and trend detection, and stream analysis.
- Presents a survey of text visualization techniques and looks at the multilingual text classification problem.
- Discusses the issue of cybercrime associated with chatrooms.
- Features advances in visual analytics and machine learning along with illustrative examples.
- Is accompanied by a supporting website featuring datasets.
Applied mathematicians, statisticians, practitioners and students in computer science, bioinformatics and engineering will find this book extremely useful.