NLPIR Semantic Intelligence: Big Data and Talent Become the Bottleneck of Industry Development

　　Big data refers to data with traceable, analyzable, and quantifiable characteristics. The "big" in the concept of big data refers to the two characteristics of "volume" and "variety" that "big data" should have.
　　With the huge potential economic value and social value brought by big data, these values ​​must be released through the effective integration, analysis and mining of data. Data integration is a necessary work for building a data warehouse. There are many solutions and software tools for the integration of structured data. The current challenge is the fusion and integration of unstructured data, such as: text data, image data, signal data, audio data, video data, etc.
　　Data mining is a process of extracting hidden, unknown but potentially useful information and knowledge from a large amount of incomplete, noisy, fuzzy random data stored in databases, data warehouses or other information repositories. The form of expression is: rules, concepts, laws and patterns. Data mining is a broad cross-discipline that combines database technology, artificial intelligence, statistics and other fields from a new perspective, and explores novel, effective, potentially useful and ultimately understandable data from a deeper level. model. In data mining, data is divided into training data, test data, and application data. The key to data mining is to find facts in training data, use test data as the basis for testing and revising theories, and apply knowledge to data.
　　NLPIR Big Data Semantic Intelligence Teaching and Research Platform is a comprehensive teaching and research platform for big data semantic intelligence analysis major. The platform is centered on natural language understanding, combined with the BIT team's years of scientific research and front-line teaching experience, and is committed to improving the level of students' big data and artificial intelligence teaching and training, scientific research and engineering practice in a scientific and rigorous way.
　　The NLPIR Big Data Semantic Intelligent Teaching and Research Platform has a complete and rich teaching system, including course materials, video teaching, practical training platform, experimental verification and project cases.
　　The NLPIR Big Data Semantic Intelligence Teaching and Research Platform is rich in teaching content, mainly focusing on the three core areas of big data, artificial intelligence and natural language understanding. The core content includes the following aspects:
　　1) Scientific view of big data: the definition of big data, the origin of scientific development; how to treat big data scientifically? Big data view.
　　2) Big data technology platform and architecture: cloud computing technology and open source platform construction; Hadoop, Spark and other data architectures, computing paradigms and application practices; TensorFlow deep learning platform.
　　3) Machine learning and common data mining: common machine learning algorithms: Bayes, SVM, deep neural network, etc.; common data mining techniques: association rule mining, classification, clustering, singularity analysis; deep learning: CNN, RNN, LSTM, Attention model, seq2seq model.
　　4) Big data semantic precision search: the contradiction between general search engine and big data vertical business; the basic technology of big data precision search: fast incremental inverted index, structured and unstructured data fusion, big data sorting algorithm, semantic association , automatic caching and optimization mechanism; big data precise search syntax: proximity search, compound search, sentiment search, precise search;
　　5) unstructured big data semantic mining
　　Semantic understanding basis: ICTCLAS and Chinese word segmentation; content key semantic automatic indexing and Automatic generation of word cloud; big data clustering; big data classification and information filtering; big data deduplication and automatic summarization; sentiment analysis and sentiment calculation
　　; Concept; automatic discovery of knowledge points; knowledge big data generation based on bootstrapping;
　　7) NLPIR intelligent semantic platform: NLPIR intelligent semantic analysis online cloud service; NLPIR Parser semantic analysis platform training; NLPIR intelligent semantic secondary development interface and tutorial.
　　8) Analysis and review of big data application cases: State Grid big data application case; new media communication innovation and headline application; unstructured big data mining.
　　According to data, there are 1.95 million AI professionals worldwide, and there is a big gap between China's senior AI talents with more than 10 years of experience compared with the United States. At present, China relies more on the introduction of a large number of overseas talents in the frontier field of artificial intelligence development. After all, high-level related talents are extremely scarce in China. The NLPIR Big Data Semantic Intelligent Teaching and Research Platform is to set up artificial intelligence-related educational resources in a targeted manner to build an artificial intelligence talent team from the source.