Now showing items 1-6 of 6

    • Can who-edits-what predict edit survival? 

      Yardim, A. B.; Maystre, L.; Kristof, V.; Grossglauser, M. (Association for Computing Machinery, 2018)
      As the number of contributors to online peer-production systems grows, it becomes increasingly important to predict whether the edits that users make will eventually be beneficial to the project. Existing solutions either ...
    • Cluster based collaborative filtering with inverted indexing 

      Subakan, Özlem Nurcan (Bilkent University, 2005)
      Collectively, a population contains vast amounts of knowledge and modern communication technologies that increase the ease of communication. However, it is not feasible for a single person to aggregate the knowledge of ...
    • Cluster searching strategies for collaborative recommendation systems 

      Altingovde, I. S.; Subakan, Ö. N.; Ulusoy, Ö. (2013)
      In-memory nearest neighbor computation is a typical collaborative filtering approach for high recommendation accuracy. However, this approach is not scalable given the huge number of customers and items in typical commercial ...
    • Location recommendations for new businesses using check-in data 

      Eravci, Bahaeddin; Bulut, Neslihan; Etemoğlu, C.; Ferhatosmanoğlu, Hakan (IEEE, 2016-12)
      Location based social networks (LBSN) and mobile applications generate data useful for location oriented business decisions. Companies can get insights about mobility patterns of potential customers and their daily habits ...
    • Software design, implementation, application, and refinement of a Bayesian approach for the assessment of content and user qualities 

      Türk, Melihcan (Bilkent University, 2011)
      The internet provides unlimited access to vast amounts of information. Technical innovations and internet coverage allow more and more people to supply contents for the web. As a result, there is a great deal of material ...
    • Towards a quality service layer for Web 2.0 

      Schaal, M.; Davenport, David; Çevik, Ali Hamdi (Springer, 2011-12)
      Despite the help of search engines and Web directories, identifying high quality content becomes increasingly difficult as the Internet gets ever more crowded with information. Prior approaches for filtering and searching ...