报告摘要：大数据面向异构自治的多源海量数据, 旨在挖掘数据间复杂且演化的关联。 Big Data Knowledge Engineering (BigKE) Starting from the HACE theorem of big data, from the perspective of big knowledge modeling, it aims to use massive, low-quality, and disorderly fragmented knowledge to build new knowledge generation And knowledge service platform. Big wisdom can only be generated when big knowledge is effectively applied to complex environments for problem solving. This report introduces the HACE theorem, BigKE model and the core elements of the Great Intelligence System, namely HI+AI+OI forms HAO intelligence, analysis And exemplify HAO intelligent services in artificial intelligence research and development in the industry. Introduction: Wu Xindong, Chief Scientist of Minglue Technology Group and Dean of Minglue Academy of Sciences, Dean of the Institute of Knowledge Science of Hefei University of Technology, National Distinguished Expert, Yangtze River Scholar, Overseas Outstanding Youth, IEEE Fellow, AAAS Fellow, a new generation of marketing smart country The head of the artificial intelligence open innovation platform, the chief scientist of the key special project of the national key research and development plan “the basic theory of big data knowledge engineering and its application research”, and the director of the “big data knowledge engineering” key laboratory of the Ministry of Education (Hefei University of Technology). Because of “pioneer contribution in the field of data mining and its application”, he won the IEEE Computer Society Technology Progress Award in 2012. The chief editor of KAIS (Knowledge and Information Systems) journal and the co-editor of TKDD (ACM Transactions on Knowledge Discovery from Data), the founder and chairman of the steering committee of ICDM (IEEE International Conference on Data Mining). From January 2005 to December 2008, he served as the editor-in-chief of IEEE Transactions on Knowledge and Data Engineering (TKDE) for two sessions. In 2014, he won the IEEE ICDM Ten-Year Most Influential Thesis Award and the Outstanding Doctoral Dissertation Award of the China Computer Society (Supervisor).
报告题目：HAO智能：HI + AI + OI
报告摘要：大数据面向异构自治的多源海量数据, 旨在挖掘数据间复杂且Evolutionary association. Big Data Knowledge Engineering (BigKE) Starting from the HACE theorem of big data, from the perspective of big knowledge modeling, it aims to use massive, low-quality, and disorderly fragmented knowledge to build new knowledge generation And knowledge service platform. Big wisdom can only be generated when big knowledge is effectively applied to complex environments for problem solving. This report introduces the HACE theorem, BigKE model and the core elements of the Great Intelligence System, namely HI+AI+OI forms HAO intelligence, analysis And exemplify HAO intelligent services in artificial intelligence research and development in the industry. Introduction: Wu Xindong, Chief Scientist of Minglue Technology Group and Dean of Minglue Academy of Sciences, Dean of the Institute of Knowledge Science of Hefei University of Technology, National Distinguished Expert, Yangtze River Scholar, Overseas Outstanding Youth, IEEE Fellow, AAAS Fellow, a new generation of marketing smart country The head of the artificial intelligence open innovation platform, the chief scientist of the key special project of the national key research and development plan “the basic theory of big data knowledge engineering and its application research”, and the director of the “big data knowledge engineering” key laboratory of the Ministry of Education (Hefei University of Technology). Because of “pioneer contribution in the field of data mining and its application”, he won the IEEE Computer Society Technology Progress Award in 2012. The chief editor of KAIS (Knowledge and Information Systems) journal and the co-editor of TKDD (ACM Transactions on Knowledge Discovery from Data), the founder and chairman of the steering committee of ICDM (IEEE International Conference on Data Mining). From January 2005 to December 2008, he served as the editor-in-chief of IEEE Transactions on Knowledge and Data Engineering (TKDE) for two sessions. In 2014, he won the IEEE ICDM Ten-Year Most Influential Thesis Award and the Outstanding Doctoral Dissertation Award of the China Computer Society (Supervisor).