The most commonly used retrieval language in library and information science is natural language. Natural language is the actual language taken from literature information and does not need standardization. The logo word is taken directly from the word of the intelligence information itself.
Natural language processing (NLP) refers to the ability of machines to understand and explain the way people write and speak.
The goal of NLP is to make computers/machines as intelligent as humans in understanding languages. The ultimate goal is to build a bridge between human communication (natural language) and computer understanding (machine language).
Natural language processing is a sub-field of artificial intelligence. The applications of natural language processing include machine translation, sentiment analysis, intelligent question answering, information extraction, language input, public opinion analysis, knowledge mapping, etc. It is also a branch of deep learning.
There are two subsets under this concept, namely natural language understanding (NLU) and natural language generation (NLG).
Apply a picture of Baidu and show their relationship as follows.
(1) The bottom layer is the most basic big data, machine learning, linguistics;
(2) Looking up, it is a knowledge map, including entity map, attention map and intention map.
(3) At the next level, language understanding is on the left and language generation is on the right.
-Language understanding, including query understanding, text understanding, emotional analysis, etc. And lexical, syntactic and semantic analysis at different levels.
-Language generation, including writing and reading comprehension.
(4) The top layer is the system layer, including question answering system, machine translation and dialogue system.