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Summary:

This book provides a systematic review of many advanced techniques to support the analysis of large collections of documents, ranging from the elementary to the profound, covering all the aspects of the visualization of text documents. Particularly, we start by introducing the fundamental concept of information visualization and visual analysis, followed by a brief survey of the field of text visualization and commonly used data models for converting document into a structured form for visualization. Then we introduce the key visualization techniques including visualizing document similarity, content, sentiments, as well as text corpus exploration system in details with concrete examples in the rest of the book.

Table of Contents:

• Acknowledgements; Contents; 1 Introduction; 1.1 Information Visualization; 1.2 Text Visualization; 1.3 Book Outline; References; 2 Overview of Text Visualization Techniques; 2.1 Review Scope and Taxonomy; 2.2 Visualizing Document Similarity; 2.2.1 Projection Oriented Techniques; 2.2.2 Semantic Oriented Techniques; 2.3 Revealing Text Content; 2.3.1 Summarizing a Single Document; 2.3.2 Showing Content at the Word Level; 2.3.3 Visualizing Topics; 2.3.4 Showing Events and Storyline; 2.4 Visualizing Sentiments and Emotions; 2.5 Document Exploration Techniques; 2.5.1 Distortion Based Approaches.
• 2.5.2 Exploration Based on Document Similarity2.5.3 Hierarchical Document Exploration; 2.5.4 Search and Query Based Approaches; 2.6 Summary of the Chapter; References; 3 Data Model; 3.1 Data Structures at the Word Level; 3.1.1 Bag of Words and N-Gram; 3.1.2 Word Frequency Vector; 3.2 Data Structures at the Syntactical-Level; 3.3 Data Models at the Semantic Level ; 3.3.1 Network Oriented Data Models; 3.3.2 Multifaceted Entity-Relational Data Model; 3.4 Summary of the Chapter; References; 4 Visualizing Document Similarity; 4.1 Projection Based Approaches; 4.1.1 Linear Projections.
• 4.1.2 Non-linear Projections4.2 Semantic Oriented Techniques; 4.3 Conclusion; References; 5 Visualizing Document Content; 5.1 ̀Ẁhat We Say'': Word; 5.1.1 Frequency; 5.1.2 Frequency Trend; 5.2 ̀̀How We Say'': Structure; 5.2.1 Co-occurrence Relationships; 5.2.2 Concordance Relationships; 5.2.3 Grammar Structure; 5.2.4 Repetition Relationships; 5.3 ̀Ẁhat Can Be Inferred'': Substance; 5.3.1 Fingerprint; 5.3.2 Topics; 5.3.3 Topic Evolutions; 5.3.4 Event; 5.4 Summary of the Chapter; References; 6 Visualizing Sentiments and Emotions; 6.1 Introduction; 6.2 Visual Analysis of Customer Comments.
• 6.3 Visualizing Sentiment Diffusion6.4 Visualizing Sentiment Divergence in Social Media; 6.5 Conclusion; References.

Author/Creator:

Cao, Nan , author

Contributors:

Cui, Weiwei , author

Languages:

English

Language Notes:

Item content: English

Main Work:

Introduction to text visualization [by Cao, N.]

Related Series:

Atlantis briefs in artificial intelligence; volume 1

Subjects:

Information visualization

General Notes:

Includes bibliographical references.
Description based on: Online resource; title from PDF title page (SpringerLink, viewed October 27, 2016).

Physical Description:

1 online resource (viii, 114 pages) : illustrations (some color).

Digital Characteristics:

text file

Call Numbers:

QA76.9.I52 C366 2016eb

ISBNs:

9789462391864 (electronic bk.)
9462391866 (electronic bk.)
9789462391857 (print) [Invalid]

Other Standard Numbers:

Digital Object Identifier: 10.2991/978-94-6239-186-4

OCLC Numbers:

961258972