Linking Behavioral Patterns to Personal Attributes through Data Re-Mining
A fundamental challenge in behavioral informatics is the development of methodologies and systems that can achieve its goals and tasks, including behavior pattern analysis. This study presents such a methodology, that can be converted into a decision support system, by the appropriate integration of existing tools for association mining and graph visualization. The methodology enables the linking of behavioral patterns to personal attributes, through the re-mining of colored association graphs that represent item associations. The methodology is described and mathematically formalized, and is demonstrated in a case study related with retail industry.
Ertek, G., Demiriz, A., Çakmak, F. (2012) “Linking Behavioral Patterns to Personal Attributes through Data Re-Mining” in Behavior Computing: Modeling, Analysis, Mining and Decision. Eds: Longbing Cao, Philip S. Yu. Springer.
Note: This is the final draft version of this paper. Please cite this paper (or this final draft) as above.
Dr. Gürdal Ertek @ Social Web:
You may be interested
Learning and Personal Attributes of University Students in Predicting and Classifying the Learning Styles:Dr. Gurdal Ertek - December 8, 2017
[caption id="attachment_1093" align="alignnone" width="707"] Fig. 1. The nine-region learning style grid[/caption] Learning and Personal Attributes of University Students in Predicting…
A Framework for Mining RFID Data From Schedule-Based SystemsDr. Gurdal Ertek - November 24, 2017
[caption id="attachment_1082" align="alignnone" width="1019"] Fig. 1. A schedule-based system where entities entering and exiting the system are tracked with RFID.[/caption]…