Now showing items 1-8 of 8

    • Automated construction of fuzzy event sets and its application to active databases 

      Saygin, Y.; Ulusoy, Özgür (IEEE, 2001)
      Fuzzy sets and fuzzy logic research aims to bridge the gap between the crisp world of math and the real world. Fuzzy set theory was applied to many different areas, from control to databases. Sometimes the number of events ...
    • Clustered linear regression 

      Ari, B.; Güvenir, H. A. (Elsevier, 2002)
      Clustered linear regression (CLR) is a new machine learning algorithm that improves the accuracy of classical linear regression by partitioning training space into subspaces. CLR makes some assumptions about the domain and ...
    • Exploiting data mining techniques for broadcasting data in mobile computing environments 

      Saygin, Y.; Ulusoy, Özgür (IEEE, 2002)
      Mobile computers can be equipped with wireless communication devices that enable users to access data services from any location. In wireless communication, the server-to-client (downlink) communication bandwidth is much ...
    • Hypergraph models and algorithms for data-pattern-based clustering 

      Ozdal, M. M.; Aykanat, Cevdet (Springer, 2004)
      In traditional approaches for clustering market basket type data, relations among transactions are modeled according to the items occurring in these transactions. However, an individual item might induce different relations ...
    • A learning-based schedulıng system wıth continuous control and update structure 

      Metan, Gökhan (Bilkent University, 2005)
      In today’s highly competitive business environment, the product varieties of firms tend to increase and the demand patterns of commodities change rapidly. Especially for high tech industries, the product life cycles ...
    • Maximizing benefit of classifications using feature intervals 

      İkizler, Nazlı; Güvenir, H. Altay (Springer, Berlin, Heidelberg, 2003)
      There is a great need for classification methods that can properly handle asymmetric cost and benefit constraints of classifications. In this study, we aim to emphasize the importance of classification benefits by means ...
    • Prescription Fraud detection via data mining : a methodology proposal 

      Aral, Karca Duru (Bilkent University, 2009)
      Fraud is the illegitimate act of violating regulations in order to gain personal profit. These kinds of violations are seen in many important areas including, healthcare, computer networks, credit card transactions and ...
    • A privacy-preserving solution for the bipartite ranking problem on spark framework 

      Faramarzi, Noushin Salek (Bilkent University, 2017-08)
      The bipartite ranking problem is defined as finding a function that ranks positive instances in a dataset higher than the negative ones. Financial and medical domains are some of the common application areas of the ranking ...