Abstract
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.
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Acknowledgements
The authors thank İlhan Karabulut for her work that inspired this research, Ahmet Şahinöz for creating colored graphs with the earlier datasets, that inspired the final form of the graphs. The authors thank Samet Bilgen, Dilara Naibi, Ahmet Memişog̃lu, and Namık Kerenciler for collecting the data used in the study, and to Didem Cansu Kurada for her insightful suggestions regarding the study.
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Ertek, G., Demiriz, A., Cakmak, F. (2012). Linking Behavioral Patterns to Personal Attributes Through Data Re-Mining. In: Cao, L., Yu, P. (eds) Behavior Computing. Springer, London. https://doi.org/10.1007/978-1-4471-2969-1_12
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DOI: https://doi.org/10.1007/978-1-4471-2969-1_12
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