88 search results - page 2 / 18 » Context-based splitting of item ratings in collaborative fil... |
ICDIM
2007
IEEE
13 years 5 months ago
2007
IEEE
In collaborative filtering systems, a common technique is default voting. Unknown ratings are filled with a default value to alleviate the sparsity of rating databases. We show ...
AAAI
2012
11 years 7 months ago
2012
To solve the sparsity problem in collaborative filtering, researchers have introduced transfer learning as a viable approach to make use of auxiliary data. Most previous transfer...
EPIA
2009
Springer
13 years 8 months ago
2009
Springer
Abstract. In this paper we propose an incremental item-based collaborative filtering algorithm. It works with binary ratings (sometimes also called implicit ratings), as it is typi...
CORR
2007
Springer
13 years 4 months ago
2007
Springer
Rating-based collaborative filtering is the process of predicting how a user would rate a given item from other user ratings. We propose three related slope one schemes with pred...
SDM
2010
SIAM
13 years 3 months ago
2010
SIAM
Collaborative filtering is an important topic in data mining and has been widely used in recommendation system. In this paper, we proposed a unified model for collaborative fil...