Relation based image retrival in online social network
Najeeb Elahi, Randi Karlsen · 2014
Online social networks allow users to share their photos with friend, family and the community at large. Social networks are formed with a number of users connected through different relationships, and the strength of these relationships has an influence on the way users react on each other photos. In this paper we investigate how we can assist users to retrieve the most relevant images from their social network. We propose Relation-Based Image Retrieval (RBIR), where social relationships are of central importance. For each user we calculate their relationships with other members in the network, and a ranked list of the closest and most reputed friends is compiled by analyzing the mutual activates between two users and their overall individual reputation in the social network. Comments and likes made by highly ranked members hold more weight, and photos are ranked in accordance with the number and weight of likes and comments they receive. To test our approach, we developed a prototype based on the Facebook platform, allowing users to search for images among their Facebook friends. The results demonstrate that our techniques are useful for retrieving relevant images.