Personalized search on Flickr based on searcher's preference prediction

Dongyuan Lu, Qiudan Li

Abstract: In this paper, we propose a personalized search model to assist users in obtaining interested photos on Flickr, which exploits the favorite marks of the searcher's friends to predict the searcher's preference on the returned photos. The proposed model utilizes a co-clustering method to extract latent interest dimensions from users' implicit interests, and employs a discriminative learning method to predict searcher's preference on the returned photos. Preliminary experiments demonstrate the improvement of the proposed model compared to existing one-fit-all methods and a user-based collaborative filtering method.