The enormous number of questions needed to acquire a full preference model when the size of the outcome space is large forces us to work with partial models that approximate the u...
We propose a new matrix completion algorithm— Kernelized Probabilistic Matrix Factorization (KPMF), which effectively incorporates external side information into the matrix fac...
This paper describes a new method for providing recommendations tailored to a user's preferences using text mining techniques and online technical specifications of products....
Alexander Yates, James Joseph, Ana-Maria Popescu, ...
Recommender systems are intelligent applications that help on-line users to tackle information overload by providing recommendations of relevant items. Collaborative Filtering (CF...
The rapid propagation of the Internet and information technologies has changed the nature of many industries. Fast response and personalized recommendations have become natural tr...