Mining Relationship Graphs for Effective Business Objectives
Conference Proceeding Article
Modern organization has two types of customer profiles: active and passive. Active customers contribute to the business goals of an organization, while passive customers are potential candidates that can be converted to active ones. Existing KDD techniques focused mainly on past data generated by active customers. The insights discovered apply well to active ones but may scale poorly with passive customers. This is because there is no attempt to generate know-how to convert passive customers into active ones. We propose an algorithm to discover relationship graphs using both types of profile. Using relationship graphs, an organization can be more effective in realizing its goals.
Databases and Information Systems | Numerical Analysis and Scientific Computing
Data Management and Analytics
6th International Conference on Knowledge Discovery and Data Mining (PAKDD-02)
City or Country
ONG, Kok-Leong; LIM, Ee Peng; and NG, Wee-Keong.
Mining Relationship Graphs for Effective Business Objectives. (2002). 6th International Conference on Knowledge Discovery and Data Mining (PAKDD-02). Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/979
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