| Summary: | 博士 === 元智大學 === 管理學院博士班 === 103 === We aimed to apply visualized data mining technique to establish a mechanism for bogus entity detection. In the past research, we collected datasets related to a large bogus entities group and their tax records, analyzing and extracting characteristics of crime. In this project, relevant datasets from large databases of 8 different systems at the Fiscal Information Agency will be integrated, examined, and extracted for tax evasion pattern recognition and for prior/ex crime behavior analysis.
Based on DMAIC (Define, Measure, Analyze, Improve, and Control), we expect to build up a detection mechanism, to define its ontology, including data, models, parameters and results, with visualized data mining technique. We also expect to discuss open data issues, such as its possible applications, legal and safety, data management, planning for data mining and data analysis, as well as the possible social impact.
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