A Personalized Recommendation on the Basis of Item Based Algorithm
- Mayuri P. chaudhari, Ganesh Dhanokar
Content-based image suggestion (CBIS) addresses the satisfaction of users long-term needs for ‘‘relevant’’ and ‘‘novel’’ images. In this paper, we present VCC-FMM, a flexible mixture model that clusters both images and users into separate groups. Then, we propose long-term relevance feedback to maintain accurate modeling of growing image collections and changing user long-term needs over time. Experiments on a real data set show merits of our approach in terms of image suggestion accuracy and efficiency. & 2010 Elsevier Ltd. All rights reserved.