picSEEK: Collaborative filtering for context-based image recommendation

As we all know, the World Wide Web is becoming a large source of images. Thus, it is manifest that the demand for image recommendation systems is increasing rapidly. There are several image recommendation systems for both commercial and academic areas, which deals with the user preference being fixed. However, since the Images preferred by a user may change depending on the contexts, the conventional systems could fail to achieve its goal due to inherent problems. Therefore, Our approach, through this paper, proposes a context-aware image recommendation service (picSEEK) that exploits the collaborative-filtering to recommend appropriate images with respect to the context. We have analyzed the recommendation process and performed a subjective test to show the usefulness of the proposed system.