How to Use Deep Learning Technology to Solve Research Related to Natural Language Processing ?

In recent years, deep learning methods have been widely used in many natural language processing fields. With the development of deep learning and related technologies, research in the field of NLP has made breakthroughs one after another. Researchers have designed various models and methods to solve NLP All kinds of problems.

As an important research direction in the intersection of computer science and artificial intelligence, NLP integrates the knowledge and achievements of linguistics, computer science, logic, psychology, artificial intelligence and other disciplines. Its main research tasks include part-of-speech tagging, machine translation, named entity recognition, machine question answering, sentiment analysis, automatic summarization, syntactic analysis, and coreference resolution, etc. Natural language is a highly abstract symbolic system, and the relationship between texts is difficult to measure. Related research highly relies on artificially constructed features.

The advantage of the deep learning method lies in its powerful discriminative ability and feature self-learning ability, which is very suitable for the characteristics of natural language with high dimensionality, no labels and big data.