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The key words of practical R are
Natural language processing studies all kinds of theories and methods to realize effective communication between people and computers with natural language. Natural language processing is not the study of natural language in general, but the development of a computer system, especially a software system, which can effectively realize natural language communication. So it is a part of computer science.
The relationship between data mining, machine learning and natural language processing, there are both intersections and differences between data mining, machine learning and natural language processing, they are interrelated and mutually utilized, and they have their own different fields and applications. Natural language processing is not the study of natural language in general, but the development of a computer system, especially a software system, which can effectively realize natural language communication.
Future Prospect of Natural Language Processing
In the field of natural language processing, two research methods based on rules and statistics alternately occupy the dominant position, and both of them have encountered bottlenecks. After the rule-based and traditional machine learning methods reach a certain stage, it is difficult to make a greater breakthrough. It is not until the improvement of computing power and data storage that the development of natural language processing is greatly promoted. The breakthrough of speech recognition makes deep learning technology very popular.
Machine translation has also made great progress. At present, Google Translate uses deep neural network technology to raise machine translation to a new height, even if it can't meet the standards of manual translation, it can meet most of the needs.
Information extraction has also become more intelligent, which can better understand the complex sentence structure and the relationship between entities and extract correct facts. Deep learning promotes the progress of natural language processing tasks, and at the same time, natural language processing tasks also provide a broad application prospect for deep learning, which makes people invest more in algorithm design.
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