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Knowledge Discovery in Enterprise Databases for Forecasting New Product Success

  • Marcin RelichEmail author
  • Krzysztof Bzdyra
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9375)

Abstract

This paper presents the knowledge discovery process that aims to improve the forecast quality of the success of new product development projects. The critical success factors for new product development are identified on the basis of information acquired from an enterprise system, including the fields of sales and marketing, research and development, production, and project management. The proposed knowledge discovery process consists of stages such as data selection from enterprise databases, data preprocessing, data mining, and the use of the discovered patterns for forecasting new product success. The illustrative example presents the use of fuzzy neural networks for forecasting net profit from new products.

Keywords

Knowledge retrieval Data mining Fuzzy neural systems New product development Rule-based systems 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Faculty of Economics and ManagementUniversity of Zielona GoraZielona GoraPoland
  2. 2.Faculty of Electronic and Computer EngineeringKoszalin University of TechnologyKoszalinPoland

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