Text Mining for Information Professionals : An Uncharted Territory / by Manika Lamba, Margam Madhusudhan.

Format:

Book

Author/Creator:

Lamba, Manika., Author.

Madhusudhan, Margam., Author.

Contributor:

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

Language:

English

Subjects (All):

Data mining.

Library science.

Application software.

Data Mining and Knowledge Discovery.

Library Science.

Computer and Information Systems Applications.

Local Subjects:

Data Mining and Knowledge Discovery.

Library Science.

Computer and Information Systems Applications.

Physical Description:

1 online resource (XVI, 356 pages) : 164 illustrations, 139 illustrations in color.

Edition:

1st ed. 2022.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2022.

System Details:

text file PDF

Summary:

This book focuses on a basic theoretical framework dealing with the problems, solutions, and applications of text mining and its various facets in a very practical form of case studies, use cases, and stories. The book contains 11 chapters with 14 case studies showing 8 different text mining and visualization approaches, and 17 stories. In addition, both a website and a Github account are also maintained for the book. They contain the code, data, and notebooks for the case studies; a summary of all the stories shared by the librarians/faculty; and hyperlinks to open an interactive virtual RStudio/Jupyter Notebook environment. The interactive virtual environment runs case studies based on the R programming language for hands-on practice in the cloud without installing any software. From understanding different types and forms of data to case studies showing the application of each text mining approaches on data retrieved from various resources, this book is a must-read for all library professionals interested in text mining and its application in libraries. Additionally, this book will also be helpful to archivists, digital curators, or any other humanities and social science professionals who want to understand the basic theory behind text data, text mining, and various tools and techniques available to solve and visualize their research problems. .

Contents:

1. The Computational Library

2. Text Data and Where to Find Them?

3. Text Pre-Processing

4. Topic Modeling

5. Network Text Analysis

6. Burst Detection

7. Sentiment Analysis

8. Predictive Modeling

9. Information Visualization

10. Tools and Techniques for Text Mining and Visualization

11. Text Data and Mining Ethics.

Other Format:

Printed edition:

ISBN:

978-3-030-85085-2

9783030850852

Access Restriction:

Restricted for use by site license.