Text Analytics: An Introduction to the Science and Applications of Unstructured Information Analysis

Are you finding it challenging to manage and understand large electronic textual sources?Do you want to be able to extract textual information and automatically discover and /or detect hidden patterns, valuable to your organization?Do you want to understand the computational approaches and develop applications for automatically analyzing and mining textual information or documents? If you answered affirmatively, this book is the right for you as it will help you get familiarized with the introductory concepts of text analytics and text mining science and applications. It will allow you to examine and analyze electronic unstructured information in order to discover patterns and gain insights that can be useful for making better decisions in your organization.Discovered patterns can further be converted into structured data, which can be analyzed and placed (or used) together with traditional decision support systems (i.e., business intelligence, relational databases, data warehouses). Text analytics applications cross-cut different domains in business, industry, science, technology both in private and public areas, hence this book becomes a key tool to decision makers.For a better understanding, each of the book's nine chapters combine basic theories, models and computational methods with step-by-step practical exercises using the Python programming language. Thus, the book introduces both the fundamentals of text analytics (i.e., natural-language processing, document representation) and different tasks, that can be conducted for different applications, including: information extraction, patterns discovery, semantic analysis, document clustering, topic modeling, and text categorization.

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