Semantic Analysis
Dipanjan Sarkar · Apress eBooks · 2019
Natural language understanding has gained significant importance in the last decade with the advent of machine learning and further advances like deep learning and artificial intelligence. Computers, or machines in general, can be programmed to learn specific things or perform specific operations. However, the key limitation is their inability to perceive, understand, and comprehend things like humans do. With the resurgence in popularity of neural networks and advances made in computer architecture, we now have deep learning and artificial intelligence evolving at a rapid pace and we have been engineering machines into learning, perceiving, understanding, and performing actions on their own. You may have seen or heard several of these efforts in the form of self-driving cars, computers beating experienced players in their own games like Chess and Go, and more recently chatbots. So far, we have looked at various computational, language processing, and machine learning techniques to classify, cluster, and summarize text. We also developed certain methods and programs to analyze and understand text syntax and structure. This chapter deals with methods that try to answer the question, "Can we analyze and understand the meaning and sentiment behind a body of text?"