Data mining is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cut costs, or both. It allows users to analyze data from many different dimensions or angles, categorize it and summarize the relationships identified. It is the process of finding correlations or patterns among dozens of fields in large relational databases.
Companies with a strong consumer focus - retail, financial, communication and marketing organizations, primarily use data mining today. It enables these companies to analyze the relationships among "internal" factors such as price, product positioning, staff skills, etc., and "external" factors such as economic indicators, technology, competition and customer demographics in order to determine the impact on sales, customer satisfaction, and corporate profits.
The purpose of this special issue is to capture the current state of methodologies and models for achieving sustainable business intelligence. Both theoretical and empirical research papers are encouraged.
Topics of interest include but are not limited to the following related assessments:
- Data processing
- Mining frequent patterns
- Data association
- Data correlation
- Data classification
- Data prediction
- Cluster Analysis
- Stream mining
- Graph mining
- Mining WWW
- Social impact of data mining
- Decision support systems
- Management information systems
- Expert systems
- Knowledge networks
- Knowledge discovery in databases
- Knowledge-based analysis
Deadline for submission of manuscripts: 30 November, 2010
Communication of peer review to authors: 20 February, 2011
Deadline for revised manuscripts: 31 March, 2011
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