In this work is discussed a scientific methodology concerning an intelligent algorithm oriented on financial strategy for SMEs. The paper follows the research guidelines of ‘Frascati’ manual about knowledge gain by innovative algorithms. Specifically has been applied a Support Vector Machine (SVM) algorithms predicting financial score of Small and Medium Enterprises –SMEs-. For the output results has been
executed a Rapid Miner workflow. The used approach represents a methodology to follow in order to improve a research project about financial technologies.
%0 Journal Article
%1 noauthororeditor
%A Lanzolla, Carlo
%A Colasuonno, Giuseppina
%A Milillo, Katia
%A Caputo, Gabriele
%D 2019
%J International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI)
%K Data Financial Frascati Guideline Machine Mining SMEs Score Support Vector features financial
%N 3
%P 01-12
%R 10.5121/ijscai.2019.8301
%T INTELLIGENT ALGORYTHM FOR IMMEDIATE FINANCIAL STRATEGY FOR SMES
%U https://aircconline.com/ijscai/V8N3/8319ijscai01.pdf
%V 8
%X In this work is discussed a scientific methodology concerning an intelligent algorithm oriented on financial strategy for SMEs. The paper follows the research guidelines of ‘Frascati’ manual about knowledge gain by innovative algorithms. Specifically has been applied a Support Vector Machine (SVM) algorithms predicting financial score of Small and Medium Enterprises –SMEs-. For the output results has been
executed a Rapid Miner workflow. The used approach represents a methodology to follow in order to improve a research project about financial technologies.
@article{noauthororeditor,
abstract = {In this work is discussed a scientific methodology concerning an intelligent algorithm oriented on financial strategy for SMEs. The paper follows the research guidelines of ‘Frascati’ manual about knowledge gain by innovative algorithms. Specifically has been applied a Support Vector Machine (SVM) algorithms predicting financial score of Small and Medium Enterprises –SMEs-. For the output results has been
executed a Rapid Miner workflow. The used approach represents a methodology to follow in order to improve a research project about financial technologies. },
added-at = {2022-04-14T08:01:18.000+0200},
author = {Lanzolla, Carlo and Colasuonno, Giuseppina and Milillo, Katia and Caputo, Gabriele},
biburl = {https://www.bibsonomy.org/bibtex/22a2f139c21b193d43415c803967a3bd5/leninsha},
doi = {10.5121/ijscai.2019.8301},
interhash = {491974be60b6d5c41750b52470274253},
intrahash = {2a2f139c21b193d43415c803967a3bd5},
issn = {2319-1015},
journal = {International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI)},
keywords = {Data Financial Frascati Guideline Machine Mining SMEs Score Support Vector features financial},
language = {English},
month = {Auguest},
number = 3,
pages = {01-12},
timestamp = {2022-04-14T08:01:18.000+0200},
title = {INTELLIGENT ALGORYTHM FOR IMMEDIATE FINANCIAL STRATEGY FOR SMES
},
url = {https://aircconline.com/ijscai/V8N3/8319ijscai01.pdf},
volume = 8,
year = 2019
}