Generalized Dirichlet Regression and other Compositional Models with Application to Market-share Data Mining of Information Technology Companies

Divya Ankam, Nizar Bouguila

Abstract

We explore the idea that market-shares of any given company have a linear relationship with the number of times the company/product is searched for on the internet. This relationship is critical in deducing whether the funds spent by a firm on advertisements have been fruitful in increasing the market-share of the company. To deduce the expenditure on advertisement, we consider google-trends as a replacement resource. We propose a novel regression algorithm, generalized Dirichlet regression, to solve the resulting problem with information from three different information-technology fields: internet browsers, mobile phones and social networks. Our algorithm is compared to Dirichlet regression and ordinary-least-squares regression with compositional transformations. Our results show both the relationship between market-shares and google-trends, and the efficiency of generalized Dirichlet regression model.

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Paper Citation


in Harvard Style

Ankam D. and Bouguila N. (2019). Generalized Dirichlet Regression and other Compositional Models with Application to Market-share Data Mining of Information Technology Companies.In Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-372-8, pages 158-166. DOI: 10.5220/0007708201580166


in Bibtex Style

@conference{iceis19,
author={Divya Ankam and Nizar Bouguila},
title={Generalized Dirichlet Regression and other Compositional Models with Application to Market-share Data Mining of Information Technology Companies},
booktitle={Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2019},
pages={158-166},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007708201580166},
isbn={978-989-758-372-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Generalized Dirichlet Regression and other Compositional Models with Application to Market-share Data Mining of Information Technology Companies
SN - 978-989-758-372-8
AU - Ankam D.
AU - Bouguila N.
PY - 2019
SP - 158
EP - 166
DO - 10.5220/0007708201580166