论文信息 - Commercializing computational intelligence techniques in a business intelligence application

Commercializing computational intelligence techniques in a business intelligence application

This paper reports on the commercialization of a business intelligence application deploying computational intelligence techniques. Theoretical foundations are included where appropriate, along with implementation and comparative benchmark results. Discussions on technology transfer mechanisms are included, identifying a generic framework for the commercialization of technology innovations, with a particular case study from Jordan.

Ali M. S. Zalzala | Hussein T. Al-Natsheh

[1] Arthur K. Kordon,et al. Applying Computational Intelligence - How to Create Value , 2009 .

[2] Efraim Turban,et al. Decision Support and Business Intelligence Systems (8th Edition) , 2006 .

[3] Peter Norvig,et al. Artificial Intelligence: A Modern Approach , 1995 .

[4] James C. Bezdek,et al. Clustering with a genetically optimized approach , 1999, IEEE Trans. Evol. Comput..

[5] Soumen Chakrabarti,et al. Mining the web - discovering knowledge from hypertext data , 2002 .

[6] C. Mallows,et al. A Method for Comparing Two Hierarchical Clusterings , 1983 .

[7] Ali M. S. Zalzala,et al. NOCEA: A rule-based evolutionary algorithm for efficient and effective clustering of massive high-dimensional databases , 2007, Appl. Soft Comput..

[8] Ali M. S. Zalzala,et al. Mining Comprehensible Clustering Rules with an Evolutionary Algorithm , 2003, GECCO.

[9] David L. Olson,et al. Introduction to Business Data Mining , 2005 .

[10] L. Massey,et al. Evaluating quality of text clustering with ART1 , 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

[11] Laurene V. Fausett,et al. Fundamentals Of Neural Networks , 1994 .

[12] Anil K. Jain,et al. Algorithms for Clustering Data , 1988 .