Text Mining: Concepts, Implementation, and Big Data Challenge

This book discusses text mining and different ways this type of data mining can be used to find implicit knowledge from text collections. The author provides the guidelines for implementing text mining systems in Java, as well as concepts and approaches. The book starts by providing detailed text preprocessing techniques and then goes on to provide concepts, the techniques, the implementation, and the evaluation of text categorization. It then goes into more advanced topics including text summarization, text segmentation, topic mapping, and automatic text management.

Table of Contents

Part I Foundation
Chapter 1 Introduction
Chapter 2 Text Indexing
Chapter 3 Text Encoding
Chapter 4 Text Association

Part II Text Categorization
Chapter 5 Text Categorization: Conceptual View
Chapter 6 Text Categorization: Approaches
Chapter 7 Text Categorization: Implementation
Chapter 8 Text Categorization: Evaluation

Part III Text Clustering
Chapter 9 Text Clustering: Conceptual View
Chapter 10 Text Clustering: Approaches
Chapter 11 Text Clustering: Implementation
Chapter 12 Text Clustering: Evaluation

Part IV Advanced Topics
Chapter 13 Text Summarization
Chapter 14 Text Segmentation
Chapter 15 Taxonomy Generation
Chapter 16 Dynamic Document Organization