Lingjiu Software: NLPIR Semantic Technology Data Mining Public Opinion Prediction

　　"Big data" is a popular word at present. This article analyzes the basic concepts of big data and big data analysis and the characteristics of big data. The significance of big data technology is not to master huge data information, but to professionalize these meaningful data. In other words, if big data is compared to an industry, the key to making this industry profitable is to improve the "processing ability" of data and realize the "value-added" of data through "processing". Without big data, relying on big data can provide enough favorable resources.
　　The arrival of the era of big data means the generation of massive data, which brings huge challenges to our existing data storage technology. Data storage management is almost every The difficulty that an enterprise applying big data needs to face is that 70% of the storage space of the disk is wasted and cannot be used well. With the progress of the times, big data is applied to more and more fields, and the data generated is more and more The more storage space is needed, the more storage space is needed, and the application of data information needs a very strong data space support. The huge amount of data and information is a huge challenge for senior leaders to make decisions. If senior leaders cannot comprehensively collect information, it is possible It will make one-sided decision-making in the final decision-making, which is not conducive to the correct implementation of decision-making, nor can it promote the development of work, and even affect future development. The
　　amount of data information is large, and the key is how to process the data. The generation of data is a It is a natural process, and the timeliness of data will lead to more data generation. If the information processing process does not work well, not only will the results change, but it may also lead to wrong processing results, making the decision results also Therefore, the level of data processing capability for senior leadership decision-makers requires the unified coordination of data analysis capabilities, data mining capabilities, and data integration capabilities, because the results of data processing are not only related to the direction of decision-making, but also related to To the future development trend. Therefore, the large amount of data information also has great requirements for data processing capabilities.
　　Lingjiu Software NLPIR Big Data Semantic Intelligent Analysis Platform is aimed at the comprehensive needs of big data content acquisition, editing, mining and searching, integrating precise network collection, natural The research results of language understanding, text mining and semantic search have lasted for 18 years and served 400,000 institutional users around the world. They are 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.