New trends in big data in 2018: NLPIR Semantic Intelligence Teaching and Research Platform

　　The development of big data and artificial intelligence technology has become a national strategy, and related technologies will become the next engine to promote the growth of the industry! , How to seek greater development and reform under the call of the new era is a top priority!
　　NLPIR Big Data Semantic Intelligence Teaching and Research Platform is a comprehensive teaching and research platform for big data semantic intelligence analysis majors. 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 main categories of the NLPIR big data semantic intelligence teaching and research platform include:
　　1) Scientific cognition. Cultivate students' scientific cognition concept of big data, artificial intelligence and natural language understanding.
　　2) Basic theory. Basic theories include machine learning, deep learning, and common algorithms for artificial intelligence.
　　3) Key technologies. The key technologies of the platform are based on natural language understanding, including Chinese word segmentation, new word discovery, keyword extraction, text classification and clustering accurate search, knowledge graph and other related technologies.
　　4) Tool platform. Mature tool platforms include: NLPIR semantic search and mining platform, big data platforms such as Hadoop, Spark, and Hive, and artificial intelligence platforms such as TensorFlow.
　　5) Practical application. Combined with practical problems, improve the practical application ability and secondary development ability of semantic intelligence.
　　The NLPIR Big Data Semantic Intelligence Teaching and Research Platform has rich 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) The scientific concept of big data: the definition of big data, The origin of scientific development; how to treat big data scientifically? How to grasp big data, and expound the scientific big data view from three levels of "knowledge", "microscopic" and "xiaoyi".
　　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 online 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 Foundation of
　　semantic understanding: ICTCLAS and Chinese word segmentation; automatic indexing of content key semantics 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
　　; Graph 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.
　　With the comprehensive advancement of the national big data strategy, the development of my country's big data industry has ushered in a "golden period". Data-driven innovation is gradually being integrated and applied in various fields of the economy and society, expanding new space for industry development and helping the transformation and upgrading of the industry structure. At the same time, with the in-depth implementation of national strategies such as the innovation and entrepreneurship strategy, the construction of a strong network country, and the Internet + Action Plan, it has brought new opportunities for the integrated development of emerging technologies and industries such as big data, Internet of Things, and artificial intelligence. new energy for development.