Now showing items 21-29 of 29

    • Modeling interestingness of streaming association rules as a benefit-maximizing classification problem 

      Aydın, T.; Güvenir, H. A. (Elsevier BV, 2009)
      In a typical application of association rule learning from market basket data, a set of transactions for a fixed period of time is used as input to rule learning algorithms. For example, the well-known Apriori algorithm ...
    • A natural language-based interface for querying a video database 

      Küçüktunç, O.; Güdükbay, U.; Ulusoy, Ö. (Institute of Electrical and Electronics Engineers, 2007-01)
      The authors developed a video database system called BilVideo that provides integrated support for spatiotemporal, semantic, and low-level feature queries. As a further development for this system, the authors present a ...
    • Predicting optimal facility location without customer locations 

      Yilmaz, Emre; Elbaşı, Sanem; Ferhatosmanoğlu, Hakan (ACM, 2017-08)
      Deriving meaningful insights from location data helps businesses make better decisions. One critical decision made by a business is choosing a location for its new facility. Optimal location queries ask for a location to ...
    • Predictors of sinus rhythm after electrical cardioversion of atrial fibrillation: results from a data mining project on the Flec-SL trial data set 

      Oto, E.; Okutucu, S.; Katircioglu-Öztürk, D.; Güvenir, H. A.; Karaagaoglu, E.; Borggrefe, M.; Breithardt, G.; Goette, A.; Ravens, U.; Steinbeck, G.; Wegscheider, K.; Oto, A.; Kirchhof, P. (Oxford University Press, 2017)
      Data mining is the computational process to obtain information from a data set and transform it for further use. Herein, through data mining with supportive statistical analyses, we identified and consolidated variables ...
    • Preface 

      Ünay, D.; Çataltepe, Z.; Aksoy, Selim (Springer Verlag, 2010)
      This book constitutes the refereed contest reports of the 20th International Conference on Pattern Recognition, ICPR 2010, held in Istanbul, Turkey, in August 2010. The 31 revised full papers presented were carefully ...
    • A prescription fraud detection model 

      Aral, K. D.; Güvenir H. A.; Sabuncuoğlu, T.; Akar, A. R. (Elsevier Ireland Ltd., 2012)
      Prescription fraud is a main problem that causes substantial monetary loss in health care systems. We aimed to develop a model for detecting cases of prescription fraud and test it on real world data from a large multi-center ...
    • Processing count queries over event streams at multiple time granularities 

      Ünal, A.; Saygın, Y.; Ulusoy, Ö. (Elsevier Inc., 2006-07-22)
      Management and analysis of streaming data has become crucial with its applications to web, sensor data, network traffic data, and stock market. Data streams consist of mostly numeric data but what is more interesting are ...
    • Ranking instances by maximizing the area under ROC curve 

      Guvenir, H. A.; Kurtcephe, M. (Institute of Electrical and Electronics Engineers, 2013)
      In recent years, the problem of learning a real-valued function that induces a ranking over an instance space has gained importance in machine learning literature. Here, we propose a supervised algorithm that learns a ...
    • Real time selection of scheduling rules and knowledge extraction via dynamically controlled data mining 

      Metan, G.; Sabuncuoglu, I.; Pierreval, H. (Taylor & Francis, 2010)
      A new scheduling system for selecting dispatching rules in real time is developed by combining the techniques of simulation, data mining, and statistical process control charts. The proposed scheduling system extracts ...