Natural language is the crystallization of human wisdom. Natural language processing is one of the most difficult problems in artificial intelligence, and the research on natural language processing is also full of charm and challenges. With the wide application of computers and the Internet, the number of natural language texts that can be processed by computers has grown unprecedentedly, and the demand for text mining, information extraction, cross-language information processing, human-computer interaction and other applications for massive information has grown rapidly. have a profound impact on our lives.
NLP is the study of human subjective experience. To put it more bluntly, NLP is a technique of thinking. NLP is the specific way we use language to change the state of mind and body. Its creators found some great people, studied what kind of programs they had, summed it up, and taught it to others. And believe that others can succeed if they can master these procedures.
NLP is a set of technologies, it can also be said that it is a set of modules, it can also be said that it is a set of methods, in any case, NLP is something that can magically change your life for the better, like the creativity of modern great science, Or like the insight of the ancient prophets, yes, NLP is so amazing, it can bring you an overall improvement in your life.
The diversity and complexity of natural language determine that it is often difficult for computers to fully understand natural language. In the deep mining of language, current linguistic research and computational linguistics research cannot fully understand the inner meaning of language, and fine language analysis often cannot fully solve complex practical problems. Therefore, shallow language analysis may be a feasible research route at present. On the one hand, it can extract specific key information below the language surface for requirements ; on the other hand, it takes into account the accuracy of the analysis results and the practicability of the system.
When mining and processing texts expressed in natural language, related technologies of natural language understanding and processing and information retrieval should be used. Computers need to model the inherent content expressed in natural language, convert it into a computable data structure, understand the surface level as much as possible, and further extract its deep semantic information.
Lingjiu Software NLPIR Big Data Semantic Intelligent Analysis Platform is aimed at the comprehensive needs of big data content acquisition, editing, mining and searching, and integrates the research results of precise network acquisition, natural language understanding, text mining and semantic search. It has served 400,000 people around the world for 18 years. It is a powerful tool for semantic intelligent analysis in the era of big data.
Lingjiu Software NLPIR big data semantic intelligent mining platform, in response to the needs of big data content processing, integrates the technologies of precise network acquisition, natural language understanding, text mining and network search, and provides client tools, cloud services, and secondary development interfaces. .
Lingjiu software NLPIR can meet the needs of users for processing big data texts from all angles, including the complete technical chain of big data: web crawling, text extraction, Chinese and English word segmentation, part-of-speech tagging, entity extraction, word frequency statistics, keywords Extraction, Semantic Information Extraction, Text Classification, Sentiment Analysis, Semantic Depth Extension, Traditional and Simple Coding Conversion, Automatic Phonetics, Text Clustering, etc.
In the future, data may become the biggest traded commodity. However, a large amount of data cannot be regarded as big data. The characteristics of big data are the large amount of data, the variety of data, and the maximization of the value of non-standardized data. In the context of big data, data mining technology has been widely used in all walks of life, so in order to better meet the needs of applications, we must strengthen the analysis of its characteristics, and pay attention to data mining in combination with actual needs The application of technology can promote the improvement of its application effect.