Using self-organizing map for data mining: A synthesis with accounting applications

Using self-organizing map for data mining : A synthesis with accounting applications

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.

Argyrou, ArgyrisHanken School of Economics, Helsinki, Finland(Swepub:hj)argarg (författare)
Hanken School of Economics, Helsinki, Finland (creator_code:org_t)

Ingår i:Data mining: Foundations and intelligent paradigmsBerlin : Springer, s. 321-3429783642231506

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