Association mining is the methodology within data mining that researches associations among the elements of a given set, based on how they appear together in multiple subsets of that set. Extensive literature exists on the development of efficient algorithms for association mining computations, and the fundamental motivation for this literature is that association mining reveals actionable insights and enables better policies. This motivation is proven valid for domains such as retailing, healthcare and software engineering, where elements of the analyzed set are physical or virtual items that appear in transactions. However, the literature does not prove this motivation for databases where items are \u201cderived items\u201d, rather than actual items. This study investigates the association patterns in changes of exchange rates of US Dollar, Euro and Gold in the Turkish economy, by representing the percentage changes as \u201cderived items\u201d that appear in \u201cderived market baskets\u201d, the day on which the observations are made. The study is one of the few in literature that applies such a mapping and applies association mining in exchange rate analysis, and the first one that considers the Turkish case. Actionable insights, along with their policy implications, demonstrate the usability of the developed analysis approach.<\/p>\n
Please cite this paper as follows:<\/em><\/p>\n Arabac\u0131, M., Aktu\u011f, A., Ertek, G. (2011) \u201cActionable Insights Through Association Mining of Exchange Rates: A Case Study.\u201d Proceedings of International Symposium on Innovations in Intelligent Systems and Applications 2011. (IEEE). June 15-17, 2011, Istanbul, Turkey.<\/strong><\/a><\/p>\n Dr. G\u00fcrdal Ertek recommends the following related books:<\/p>\n Essentials of Business Analytics 2nd Edition<\/em><\/a><\/p>\n