NLPIR Intelligent Semantics: Big Data Mining Helps Rapid Development of Artificial Intelligence

Artificial Intelligence (English), abbreviated as AI, also known as machine intelligence. The term "artificial intelligence" was originally coined at the Dartmouth Society in 1956. It is a comprehensive discipline developed by computer science, cybernetics, information theory, neurophysiology, psychology, linguistics and other disciplines. From the perspective of computer application systems, artificial intelligence is the study of how to create intelligent machines or intelligent systems to simulate the capabilities of human intelligence activities to extend the science of people's intelligence.

Artificial intelligence is an emerging edge discipline developed on the basis of mutual penetration of computer science, cybernetics, information theory, psychology, linguistics and other disciplines. It mainly studies the use of machines (mainly computers) to imitate and realize human intelligence. Behavior, after decades of development, artificial intelligence applications have been developed in many fields, and many places have been applied in our daily life and learning.

Artificial intelligence is a discipline that studies computers to simulate certain thinking processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), including the principle of computer-implemented intelligence, the creation of computers similar to human brain intelligence, and the making of computers. Can achieve a higher level of application. Artificial intelligence will involve disciplines such as computer science, psychology, philosophy, and linguistics. It can be said that almost all disciplines of the natural sciences and social sciences have gone far beyond the scope of computer science. The relationship between artificial intelligence and thinking science is the relationship between practice and theory. Artificial intelligence is at the level of technology application of thinking science. It is an application branch of it. From the perspective of thinking, artificial intelligence is not limited to logical thinking. It is necessary to consider image thinking and inspiration thinking to promote the breakthrough development of artificial intelligence. Mathematics is often regarded as the basic science of many disciplines. Mathematics also enters the field of language and thinking. Intelligent disciplines must also borrow mathematical tools. Mathematics not only plays a role in standard logic, fuzzy mathematics, etc., mathematics enters the discipline of artificial intelligence, and they will promote each other and develop faster.

The processing of natural language is a typical example of the application of artificial intelligence technology in practical fields. After years of hard work, this field has achieved a lot of remarkable results. At present, the main direction of the field is: how computer systems are based on themes and dialogue situations, focusing on a large amount of common sense - world knowledge and expectations, generating and understanding natural language. This is an extremely complicated coding and decoding problem.

Lingbi Software NLPIR big data semantic intelligent analysis platform for the comprehensive needs of Chinese data mining, combined with the research results of network accurate collection, natural language understanding, text mining and semantic search, has served for 400,000 institutional users worldwide for 18 years. It is a great tool for semantic intelligence analysis in the great era.

The NLPIR Big Data Semantic Intelligent Analysis Platform platform integrates natural language understanding, web search and text mining technologies for the needs of Internet content processing, and provides a basic tool set for secondary development of technology.

NLPIR can meet the application requirements of big data texts in all aspects, including the complete technology chain of big data: network acquisition, text extraction, Chinese and English word segmentation, part-of-speech tagging, entity extraction, word frequency statistics, keyword extraction, semantic information. Extraction, text categorization, sentiment analysis, semantic depth expansion, simplification and transcoding, automatic phonetic transcription, text clustering, etc.

In the information age, the importance of big data has become an industry consensus. The development trend of big data technology and application is unstoppable. How to fully and effectively analyze and mine big data, transform it into valuable information and knowledge, solve various scientific and application problems, become a major challenge in the development of information technology in the era of big data, and also The new commanding heights of information technology innovation.