Predicting future ranking of online novels based on collective intelligence
Kazunori Shimizu, Eisuke Ito, Sachio Hirokawa · Kyushu University Institutional Repository (QIR) (Kyushu University) · 2013
A large number of novels are being up- loaded as online novels. The present paper proposes a ranking algorithm based on the users’ favorite lists (bookmarks). Empirical evaluation has been conducted with respect to each genre of novels. In several genres, it is confirmed that the top ranked novels in July are predicted from the bookmarks of May.