Addressing cold-start in app recommendation
Jovian Lin, Kazunari Sugiyama, Min‐Yen Kan, Tat‐Seng Chua · 2013
As a tremendous number of mobile applications (apps) are readily available, users have difficulty in identifying apps that are relevant to their interests. Recommender systems that depend on previous user ratings (i.e., collaborative filtering, or CF) can address this problem for apps that have sufficient ratings from past users. But for apps that are newly released, CF does not have any user ratings to base recommendations on, which leads to the cold-start problem.