Deep Learning for Opinion Mining

Deep Learning for Opinion Mining

Iman Raeesi Vanani, Morteza Amirhosseini
Copyright: © 2019 |Pages: 26
DOI: 10.4018/978-1-5225-6117-0.ch003
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In this chapter, through introducing the deep learning and relation between deep learning and artificial intelligence, and especially machine learning, 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. Finally, authors have summarized different sections of the chapter at conclusion.
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Deep Learning Definition

Before talking about deep learning, relationship with Machine Learning, Artificial Intelligence, and shallow learning is necessary to know. The easiest way to understand this relationship is looking at the diagram in Figure 1.

Figure 1.

AI Diagram


Artificial Intelligence

The term AI emerged in 1956 by John McCarthy, who is also referred as Father of Artificial Intelligence. The idea behind AI is fairly simple yet fascinating, which is to make intelligent machines that can take decisions on its own. You may think it as a science fantasy, but with respect to recent developments in technology and computing power, very idea seems to come closer to reality day by day.

Nowadays, Computers have some intelligence power to all the programs that humans have created and which allow them to “do some intelligence things” that human consider useful. But there are many tasks which humans are able to do rather easily but stay out of reach of computers, at the beginning of the current century. Many of these tasks name under the label of Artificial Intelligence. Researchers believe that we could not create AI for all tasks because we do not know explicitly how to do these tasks, even though our brain can do them. Doing those tasks involve knowledge that is now implicit, but we have information about those tasks through data.

Fuzzy logic, neural networks, machine learning, evolutionary computations, pattern recognition are some of AI algorithms and methods those have been using as a solution for enabling computers to make a decision and allow them for learning.

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