Lab Manual

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IBM SPSS Modeler Text Analytics 15 User’s Guide

Note: Before using this information and the product it supports, read the general information under Notices on p. 356. This edition applies to IBM® SPSS® Modeler Text Analytics 15 and to all subsequent releases and modifications until otherwise indicated in new editions. Adobe product screenshot(s) reprinted with permission from Adobe Systems Incorporated. Microsoft product screenshot(s) reprinted with permission from Microsoft Corporation. Licensed Materials - Property of IBM

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Preface

IBM® SPSS® Modeler Text Analytics offers powerful text analytic capabilities, which use advanced linguistic technologies and Natural Language Processing (NLP) to rapidly process a large variety of unstructured text data and, from this text, extract and organize the key concepts. Furthermore, SPSS Modeler Text Analytics can group these concepts into categories. Around 80% of data held within an organization is in the form of text documents—for example, reports, Web pages, e-mails, and call center notes. Text is a key factor in enabling an organization to gain a better understanding of their customers’ behavior. A system that incorporates NLP can intelligently extract concepts, including compound phrases. Moreover, knowledge of the underlying language allows classification of terms into related groups, such as products, organizations, or people, using meaning and context. As a result, you can quickly determine the relevance of the information to your needs. These extracted concepts and categories can be combined with existing structured data, such as demographics, and applied to modeling in IBM® SPSS® Modeler’s full suite of data mining tools to yield better and more-focused decisions. Linguistic systems are knowledge sensitive—the more information contained...