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Springer Text Mining - Predictive Methods for Unstructured Data

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Description

Explore the intersection of data mining and unstructured information with Text Mining: Predictive Methods for Analyzing Unstructured Information by Springer. While data mining is a mature technology for processing structured numerical information, text presents a unique challenge as unstructured data. This book examines whether the same predictive methods used for numerical measurements can be applied to text. It provides a deep look into the prediction problem and how to find predictive patterns within unstructured text, bridging the gap between traditional data mining and text analysis.

Key Features

Published by Springer, this book explores predictive methods for analyzing unstructured information.

Learn how to apply data mining techniques to text, which is often categorized as unstructured data.

Examine the relationship between structured numerical measurements and unstructured text data.

Study methods for finding predictive patterns within different types of data sets.

Understand if the same methods used for numerical data can solve prediction problems in text.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
25 October 2004
Listed Since
27 December 2006

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No barcode data available

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