At present, the intelligent decision-making of domestic enterprises is progressing slowly, making it difficult to quickly promote the improvement of their core competitiveness, which will directly affect the pace of integration of Chinese enterprises with international modernization development. The main manifestations are: 1) The computing architecture for intelligent decision-making is backward. The C/S or B/S architecture adopted by traditional information technology has shortcomings such as high construction costs, serious information island effect, and failure to support high-performance computing decision-making, resulting in a backward foundation of intelligent decision-making systems. 2) Data management is backward. Traditional enterprises have serious internal data barriers, lack of data standards, and data heterogeneity directly hinders data sharing and linkage analysis, making it difficult to provide effective data for intelligent decision-making. 3) Intelligent decision-making technology innovation is difficult. Traditional decision-making technologies cannot support high-performance, parallel computing, data acquisition and processing capabilities cannot be qualitatively improved, and cannot respond to the decision-making requirements of the current big data environment, resulting in low decision-making efficiency.
In response to the above problems, this project is funded by the National 863 Plan, the National Natural Science Foundation of China, etc., with the goal of serviceization of computing architecture for intelligent decision-making, semantics of data management and innovation of decision-making technology. After more than 10 years of research and development, it has built a key technology and system for enterprise intelligent decision-making driven by data semantics, an enterprise intelligent decision-making infrastructure supported by cloud computing technology, Semantic-driven enterprise decision-making big data management and intelligent decision-making technology based on massive case reasoning achieves high performance, high sharing, and high efficiency of enterprise intelligent decision-making, and ultimately achieves scientific modernization of enterprise decision-making analysis.
The main innovation points are as follows: 1) It realizes the semantic understanding and refinement technology of decision problems based on ontology, realizes the intelligent collection of big data of decision cases based on semantics, and builds a massive decision case database. Based on this, it proposes a semantic-based decision case intelligent reasoning technology to achieve intelligent decision-making in enterprises. 2) Formulate a standard system and data model for enterprise decision-making data, and propose technologies for enterprise decision-making data collection, representation, storage and mining based on ontology semantics, so that enterprise decision-making data can be scientifically managed and efficiently shared. 3) Complete the intelligent construction of decision models based on semantic differences, realize model selection through evaluation of the ability and confidence of the decision models, and deploy dynamic combination strategies of decision services at the platform level. 4) Propose a "four-layer cloud computing" system for enterprise intelligent decision-making. Based on the traditional "IaaS" and "PaaS", we innovatively propose "Data Management as a Service DMaaS" and "Decision as a Service DSaaS" to realize the virtualization of underlying resources of the cloud platform. Elastic management and comprehensively optimize the intelligent decision-making infrastructure.
The above-mentioned core innovation points are orderly and interdependent, forming an enterprise intelligent decision support solution with distinctive technical characteristics and systematic. The project results have obtained 2 authorized invention patents, accepted 6 invention patents, formulated 2 corporate standards, and obtained 5 software copyrights. More than 50 papers have been published, including more than 30 SCI/EI searches and more than 160 citations from Google Scholar. It is currently used in 10 provinces, municipalities and autonomous regions across the country such as Shanghai, Beijing, Guangdong, Shaanxi, Shanxi, and Xinjiang. It serves more than 600 projects including China Shenhua Group and its subsidiaries, the National Bureau of Statistics, and the Shanghai Bureau of Statistics. In more than 600 projects such as national large and medium-sized enterprises, government agencies and institutions, and small and medium-sized enterprises, it has promoted many units to achieve rapid transformation in informatization and scientific management, optimized business processes, and improved the efficiency of decision support. It has produced huge social and economic benefits. From January 2011 to December 2013, the project's cumulative new output value was 591.0273 million yuan, new profits were 59.1384 million yuan, and new taxes were 26.4486 million yuan.