A Review of Research on Multi-Source Data Fusion Methods in Science and Technology Intelligence
[Research purpose]Multi source data fusion can reduce uncertainty factors such as information inconsistency and semantic am-biguity through cross referencing.Faced with the rapid increase in massive heterogeneous data from multiple sources caused by the popular-ity of big data and artificial intelligence,effective fusion has become one of the key challenges in the field of scientific and technological intelligence research.[Research method]Firstly,explain the conceptual characteristics of multi-source data based on existing defini-tions;Secondly,systematically sort out the multi-source data fusion methods based on the depth of data fusion in the text;Finally,this article analyzes the application and role of multi-source data fusion in different scientific and technological intelligence scenarios.[Re-search conclusion]From a conceptual perspective,multi-source data fusion has two directions:endogenous and exogenous.From the perspective of fusion methods,the existing commonly used methods mainly include three types:data source fusion,structural relationship fusion,and semantic fusion.Fusion methods not only achieve the transformation from physical fusion to chemical fusion,but also have been widely applied in the fields of technology development trend analysis,academic evaluation,and demand detection.Future research needs to refine feasible methods for heterogeneous weighting through practical operations,strengthen the summary and induction of fusion methods with an applicationoriented approach,and explore the formation of reusable model frameworks.
scientific and technological intelligencemulti source datamultimodal datadata fusionsemantic fusionfusion method
万方数据
维普
