Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
5-2002
Abstract
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.
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing
Publication
6th International Conference on Knowledge Discovery and Data Mining (PAKDD-02)
Identifier
10.1007/3-540-47887-6_56
Publisher
Springer Verlag
City or Country
Taipei, Taiwan
Citation
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).
Available at: https://ink.library.smu.edu.sg/sis_research/979
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://portal.acm.org/citation.cfm?id=693661
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons