Extracting Knowledge From Opinion Mining
Сетевые технологии / Базы данных
Основная информация:
Название: Extracting Knowledge From Opinion Mining
Жанр: Нет
Автор: Rashmi Agrawal, Neha Gupta
Год выпуска: 2018
Формат: PDF
Размер: 13.1 MB
ISBN: 336082818498
Язык: Английский
СКАЧАТЬ Extracting Knowledge From Opinion Mining БЕСПЛАТНО EPUB - DOC - DJVU - RTF - PDFОписание: Data mining techniques are commonly used to extract meaningful information from the web, such as data from web documents, website usage logs, and hyperlinks. Building on this, modern organizations are focusing on running and improving their business methods and returns by using opinion mining. In this book, through introducing the Deep Learning and relation between Deep Learning (DL) and Artificial Intelligence (AI), and especially Machine Learning (ML), the authors discuss machine learning and deep learning techniques, the literature focuses on applied deep learning techniques for extracting opinions. It can be found that opinion mining without using deep learning is not meaningful.
In this way, authors mention the history of deep learning and appearance of it and some important and useful deep learning algorithms for opinion mining; learning methods and customized deep learning techniques for opinion mining will also be described to understand how these algorithms and techniques are used as an applicable solution. Future trends of deep learning in opinion mining are introduced through some clues about the applications and future usages of deep learning and opinion mining and how intelligent agents develop automatic deep learning.
Extracting Knowledge From Opinion Mining is an essential resource that presents detailed information on web mining, business intelligence through opinion mining, and how to effectively use knowledge retrieved through mining operations. While highlighting relevant topics, including the differences between ontology-based opinion mining and feature-based opinion mining, this book is an ideal reference source for information technology professionals within research or business settings, graduate and post-graduate students, as well as scholars.
Contents:
Foreword.................... xvi
Preface......................xviii
Acknowledgment.............. xxvi
Section 1 Introductory Concepts of Opinion Mining
Chapter 1 Fundamentals of Opinion Mining.................1
Chapter 2 Feature Based Opinion Mining...................20
Chapter 3 Deep Learning for Opinion Mining...............40
Chapter 4 Opinion Mining: Using Machine Learning Techniques..........66
Section 2 Ontologies and Their Applications
Chapter 5 Ontology-Based Opinion Mining..........84
Chapter 6 Ontologies, Repository, and Information Mining in Component-Based Software Engineering Environment........104
Chapter 7 Ontology-Based Opinion Mining for Online Product Reviews...........123
Chapter 8 Applications of Ontology-Based Opinion Mining...........149
Section 3 Tools and Techniques of Opinion Mining
Chapter 9 Tools of Opinion Mining......................179
Chapter 10 Sentimental Analysis Tools..................204
Chapter 11 Anatomizing Lexicon With Natural Language Tokenizer Toolkit 3...........232
Section 4 Challenges and Open Issues of Opinion Mining
Chapter 12 Challenges of Text Analytics in Opinion Mining.............268
Chapter 13 Open Issues in Opinion Mining.......................283
Section 5 Case Study
Chapter 14 Case Study: Efficient Faculty Recruitment Using Genetic Algorithm...............299
Compilation of References....................... 312
About the Contributors......................... 337
Index........................ 344