Generating adequate recommendations for newcomers is a hard problem for a recommender system (RS) due to lack of detailed user profiles and social preference data. Empirical evide...
Patricia Victor, Chris Cornelis, Ankur Teredesai, ...
Data sparsity, scalability and prediction quality have been recognized as the three most crucial challenges that every collaborative filtering algorithm or recommender system conf...
Automated recommendation (e.g., personalized product recommendation on an ecommerce web site) is an increasingly valuable service associated with many databases--typically online ...
Collaborative filtering (CF) has been successfully deployed over the years to compute predictions on items based on a user's correlation with a set of peers. The black-box na...
Barry Smyth, Brynjar Gretarsson, John O'Donovan, S...
BLASTn is a ubiquitous tool used for large scale DNA analysis. Detailed profiling tests reveal that the most computationally intensive sections of the BLASTn algorithm are the sc...