Now showing items 1-4 of 4

  • Collaborative filtering based on user trends 

    Symeonidis P; Nanopoulos A; Papadopoulos A; Manolopoulos Y (Springer, 2007)
    Recommender systems base their operation on past user ratings over a collection of items, for instance, books, CDs, etc. Collaborative Filtering (CF) is a succesful recommendation technique. User ratings are not expected ...
  • Collaborative filtering process in a whole new light 

    Symeonidis P; Nanopoulos A; Papadopoulos A; Manolopoulos Y (IEEE, 2006)
    Collaborative Filtering (CF) Systems are gaining widespread acceptance in recommender systems and e-commerce applications. These systems combine information retrieval and data mining techniques to provide recommendations ...
  • Nearest-biclusters collaborative filtering with constant values 

    Symeonidis P; Nanopoulos A; Papadopoulos A; Manolopoulos Y (Springer, 2007)
    Collaborative Filtering (CF) Systems have been studied extensively for more than a decade to confront the "information overload" problem. Nearest-neighbor CF is based either on common user or item similarities, to form the ...
  • Scalable collaborative filtering based on latent semantic indexing 

    Symeonidis P; Nanopoulos A; Papadopoulos A; Manolopoulos Y (AAAI, 2006)
    Nearest-neighbor collaborative filtering (CF) algorithms are gaining widespread acceptance in recommender systems and e-commerce applications. User ratings are not expected to be independent, as users follow trends of ...