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Using self-organizing map for data mining : A synthesis with accounting applications
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- Andreev, Andriy (author)
- Hanken School of Economics, Helsinki, Finland
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- Argyrou, Argyris (author)
- Hanken School of Economics, Helsinki, Finland
- (creator_code:org_t)
- 2012-01-12
- 2012
- English.
- In: Data mining: Foundations and intelligent paradigms. - Berlin : Springer. - 9783642231506 ; , s. 321-342
- Book chapter (peer-reviewed)
Abstract
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- The self-organizing map (i.e. SOM) has inspired a voluminous body of literature in a number of diverse research domains. We present a synthesis of the pertinent literature as well as demonstrate, via a case study, how SOM can be applied in clustering accounting databases. The synthesis explicates SOM's theoretical foundations, presents metrics for evaluating its performance, explains the main extensions of SOM, and discusses its main financial applications. The case study illustrates how SOM can identify interesting and meaningful clusters that may exist in accounting databases. The paper extends the relevant literature in that it synthesises and clarifies the salient features of a research area that intersects the domains of SOM, data mining, and accounting.
Subject headings
- SAMHÄLLSVETENSKAP -- Ekonomi och näringsliv -- Företagsekonomi (hsv//swe)
- SOCIAL SCIENCES -- Economics and Business -- Business Administration (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Systemvetenskap, informationssystem och informatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Information Systems (hsv//eng)
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- ref (subject category)
- kap (subject category)
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