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 Title of the Paper:  Improving Customer 
	Satisfaction by the Expert System Using Artificial Neural Networks 
	DOWNLOAD FULL PDF Authors: Feng Qian and Linwen Xu
 Abstract: CRM, which aims to enhance the effectiveness and performance of 
	the businesses by improving the customer satisfaction and loyalty, has now 
	become a leading business strategy in highly competitive business 
	environment. The objective of this research is to improve customer 
	satisfaction on product’s colors with the aid of the expert system developed 
	by the authors by using artificial neural networks. The expert system’s role 
	is to capture the knowledge of the experts and the data from the customer 
	requirements, and then, process the collected data and form the appropriate 
	rules for choosing product’s colors. In order to identify the hidden pattern 
	of the customer’s needs, the artificial neural networks technique has been 
	applied to classify the colors based upon a list of selected information. 
	Moreover, the expert system has the capability to make decisions in ranking 
	the scores of the colors presented in the selection. In addition, the expert 
	system has been validated with a variety of customer types.
 
Keywords: Expert system; Artificial neural networks; Customer relationship 
management; Back propagation; Customer satisfaction; Decision support
 
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 Title of the Paper: The Impact of ICT on the 
	Development of Latvia as a New Member of the EU 
	DOWNLOAD FULL PDF Authors: J. Ulmanis and A. 
	Kolyshkin
 Abstract: The data from the Global Information Technology Reports (2004 – 
	2005 and 2006 – 2007), the International Benchmarking Study 2004 and similar 
	report from Latvia are used in the present paper to analyze the factors that 
	influence ICT adoption and usage. Relative strengths and weaknesses of 
	Latvia with respect to the use and adoption of information and communication 
	technologies are identified through detailed comparison with two EU 
	countries – Ireland and Estonia.. Methods of analysis include regression 
	analysis and hypotheses testing.
 Keywords: linear regression model, 
information and communication technology, hypothesis testing 
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