Ratio-based collaborative filtering algorithms
Yaqiu Liu, Zhendi Wang, Man Li · 2008
Collaborative filtering is the process of predicting how a user would rate a given item from other user ratings. we propose a new collaborative filtering algorithms, ratio-based collaborative filtering algorithms, by calculating the ratio between the ratings of one item and another for users who rated both to predict the ratings. Ratio-based collaborative filtering algorithms are easy to implement, and have reasonably accurate, by factoring in the weighted average methods and the preference parameter, we achieve results competitive with traditional memory-based algorithms over the Movielens data sets. The result is sufficient to support our claim.