Research On The Science And Technology Decision-making Support Method Based On Multi-source Data Fusion

We have entered the era of big data.Big data is gradually becoming a new model and a new element in promoting the development of social development and modernization governance systems.Effective use of massive data resources and big data analysis methods and technologies provide decision support for decision makers has become an intelligence service.One of the consensus areas of research.Under the new circumstances,how to properly implement the intelligence requirements of “eyes and ears,soldiers,and staff officers” poses new challenges to the current intelligence research.Directly focusing on users' decision-making needs and intelligence services for problem solving have become the focus of work under the big data environment.In the research of decision support for intelligence users in the field of intelligence,most of them use self-investigation and consultation methods to summarize the types of user requirements.Research and application of new methods for obtaining intelligence needs are still rare;in the data driven environment,intelligence needs It often exists in various types of information related to the target user's activities.How to comprehensively use multi-source data fusion,and use advanced analysis methods and technologies for information mining and analysis needs further exploration.Therefore,in the new era of“innovation-driven,intelligence-first”,multi-source data fusion and big data analysis methods are used to in-depth detect the needs of intelligence users and provide reference for the accuracy and individualized support of intelligence users' decisions.The main content of this study consists of three parts:(1)Framework for supporting scientific and technological decision-making based on multi-source data fusion(2)Detection of demand for scientific and technological decision-making based on multisource data fusion,detection of the needs of intelligence users,and providing important support for follow-up decision support reference.(3)Scientific and technical decisions support the mining and analysis of intelligence information.Through summarizing and analyzing,in the literature data,the supporting information of the institutional user's scientific and technological decision-making needs identified according to the above part is detected,and a complete set of scientific and technological decision-making needs and supporting information are displayed.This study has constructed an analysis framework of "Technical decision support method based on multi-source data fusion".This framework includes "methods for obtaining and extracting multi-source data","user technology decision-making demand detection methods",and "science and technology decision support information and information Mining and analysis methods" three aspects.The empirical data of this study comes from the website data of the Ministry of Science and Technology of the People's Republic of China,mass media data,and national leaders' speeches,reports,conferences,policies,and scientific and technological literature data.The semantic correlation is the starting point,and the scientific and technological decision-making needs of the intelligence users of the Ministry of Science and Technology are analyzed.As a goal,comprehensively use data mining,natural language processing,and intelligence analysis methods to dig deeper into the text to tap the key scientific and technological fields and attributes of users of the Ministry of Science and Technology;use scientific measurement methods and social network analysis methods in combination with users already detected.Decision-making needs,from the scientific and technical literature to find information that can provide support for users' technological decision-making,and form a series of decision support method.The experimental results show that this study constructs a framework of scientific and technical decision support methods based on multi-source data fusion,which realizes the proactive detection of user's intelligence needs and provides intelligence support for user's scientific and technological decision-making needs.It is a new study that actively supports users' technological decision-making.The exploration has enriched the model of intelligence services and provided a certain reference for intelligence services to become passive.