A Visualized Data Analysis for Bogus Business Entity Detection
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...
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ndltd-TW-103YZU056270032019-05-15T21:51:49Z http://ndltd.ncl.edu.tw/handle/p6jx2h A Visualized Data Analysis for Bogus Business Entity Detection 視覺化虛設行號逃漏稅預警機制建置之探討 Chih-Cheng Hsu 許志誠 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. Hilary Cheng 鄭雅穗 學位論文 ; thesis 129 zh-TW |
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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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Hilary Cheng |
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Hilary Cheng Chih-Cheng Hsu 許志誠 |
author |
Chih-Cheng Hsu 許志誠 |
spellingShingle |
Chih-Cheng Hsu 許志誠 A Visualized Data Analysis for Bogus Business Entity Detection |
author_sort |
Chih-Cheng Hsu |
title |
A Visualized Data Analysis for Bogus Business Entity Detection |
title_short |
A Visualized Data Analysis for Bogus Business Entity Detection |
title_full |
A Visualized Data Analysis for Bogus Business Entity Detection |
title_fullStr |
A Visualized Data Analysis for Bogus Business Entity Detection |
title_full_unstemmed |
A Visualized Data Analysis for Bogus Business Entity Detection |
title_sort |
visualized data analysis for bogus business entity detection |
url |
http://ndltd.ncl.edu.tw/handle/p6jx2h |
work_keys_str_mv |
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