Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/76506
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dc.contributor資管系-
dc.creatorHong, C.-F.;Chiu, T.-F.;Chiu, Y.-T.;Lin, Mu-Hua-
dc.date2007-
dc.date.accessioned2015-07-13T08:05:16Z-
dc.date.available2015-07-13T08:05:16Z-
dc.date.issued2015-07-13T08:05:16Z-
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/76506-
dc.description.abstractIn order to visualise the decision making process, the data association diagram is prepared to show the relationships or scenarios extracted from data, and provide a way for designing or discovering alternatives. However, managers are not easy to design alternatives if the collected data is large and complex. Thus, this study provides an approach for extracting the concepts from association diagrams to create the conceptual scenario diagrams. Afterward, variant diagrams are generated from the conceptual scenario diagrams for easily visualising and explaining the variation of financial status within a firm. Finally, the integrated scenario map is produced for managers to understand the financial manipulations of the firm. © Springer-Verlag Berlin Heidelberg 2007.-
dc.format.extent176 bytes-
dc.format.mimetypetext/html-
dc.relationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),Volume 4570 LNAI, Pages 886-895-
dc.relation20th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, lEA/AlE-2007,26 June 2007 through 29 June 2007,Kyoto-
dc.subjectArtificial intelligence; Decision making; Feature extraction; Large scale systems; Map symbols; Chance discovery; Conceptual scenario; Data association diagram; Association rules-
dc.titleUsing conceptual scenario diagrams and integrated scenario map to detect the financial trend-
dc.typeconferenceen
item.fulltextWith Fulltext-
item.cerifentitytypePublications-
item.openairetypeconference-
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
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