Principles of data mining
Learning missing values from summary constraints
ACM SIGKDD Explorations Newsletter
A Framework for Analysis of Data Quality Research
IEEE Transactions on Knowledge and Data Engineering
DEMON: Mining and Monitoring Evolving Data
IEEE Transactions on Knowledge and Data Engineering
Toward Multidatabase Mining: Identifying Relevant Databases
IEEE Transactions on Knowledge and Data Engineering
Aggregation of Imprecise and Uncertain Information in Databases
IEEE Transactions on Knowledge and Data Engineering
Modeling Completeness versus Consistency Tradeoffs in Information Decision Contexts
IEEE Transactions on Knowledge and Data Engineering
Integrating E-Commerce and Data Mining: Architecture and Challenges
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Guiding knowledge discovery through interactive data mining
Managing data mining technologies in organizations
A Methodology for Evaluating and Selecting Data Mining Software
HICSS '99 Proceedings of the Thirty-second Annual Hawaii International Conference on System Sciences-Volume 6 - Volume 6
Detection and Recovery Techniques for Database Corruption
IEEE Transactions on Knowledge and Data Engineering
On the Use of Conceptual Reconstruction for Mining Massively Incomplete Data Sets
IEEE Transactions on Knowledge and Data Engineering
A data cleaning solution by Perl scripts for the KDD Cup 2003 task 2
ACM SIGKDD Explorations Newsletter
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Application of data mining techniques for customer lifetime value parameters: a review
International Journal of Business Information Systems
International Journal of Business Information Systems
Using fuzzy AHP for evaluating the dimensions of data quality
International Journal of Business Information Systems
An integrative framework for customer relationship management: towards a systems view
International Journal of Business Information Systems
International Journal of Business Information Systems
Summarising customer online reviews using a new text mining approach
International Journal of Business Information Systems
Queuing system for different classes of customers
International Journal of Business Information Systems
A conceptual model for proactive-interactive customer complaint management systems
International Journal of Business Information Systems
| Hi-index | 0.00 |
Data mining is a new technology that helps businesses to predict future trends and behaviours, allowing them to make proactive, knowledge-driven decisions. When data mining tools and techniques are applied on the data warehouse based on customer records, they search for the hidden patterns and trends. These can be further used to improve customer understanding and acquisition. Customer Relationship Management (CRM) systems are adopted by the organisations in order to achieve success in the business and also to formulate business strategies, which can be formulated based on the predictions given by the data mining tools. Basically three major areas of data mining research are identified: implementation of CRM systems, evaluation criteria for data mining software and CRM systems and methods to improve data quality for data mining. The paper is concluded with a proposed integrated model for the CRM systems evaluation and implementation. This paper focuses on these areas, where there is need for more explorations, and will provide a framework for analysis of the data mining research for CRM systems.