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EnglishIn this work, we explore the application of machine learning models (MLM) to the analysis of firmsâ performance. To such aim, we consider a bunch of financial indicators on firms operating in the Information and Communication Technology (ICT) sector, with attention to enterprises providing ICT related-services. The rationale is to highlight the potential of MLM to exploit the complexity of financial data, and to offer a handy way to visualize the related information. In fact, instead of performing classical analysis, we discuss how to apply to those indicators Self-Organizing Maps-SOMsâthat are well suited to manage high dimensional and complex datasets to extract their relevant features. It emerges that SOMs are useful in clustering companies depending on multi-dimensional criteria and in analysing hidden relations in companiesâ performances.
| Titolo: | Mapping financial performances in Italian ICT-related firms via self-organizing maps |
| Autori: | |
| Data di pubblicazione: | 2018 |
| Handle: | http://hdl.handle.net/11567/901235 |
| ISBN: | 978-3-319-62635-2 978-3-319-62636-9 |
| Appare nelle tipologie: | 02.01 - Contributo in volume (Capitolo o saggio) |
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| File | Descrizione | Tipologia | |
|---|---|---|---|
| dameri_garelli_resta_springer.pdf | Documento in versione editoriale | Administrator Richiedi una copia |
http://hdl.handle.net/11567/901235
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