i AVATAR
Aixin Sun, Sourav Saha Bhowmick, Yao Liu · Proceedings of the VLDB Endowment · 2010
Tags associated with social images are valuable information source for superior image search and retrieval experiences. Due to the nature of tagging, many tags associated with images are not visually descriptive. Consequently, presence of these noisy tags may reduce the effectiveness of tags' role in image retrieval. To address this problem, we demonstrate i Avatar (interActive VisuAl-representative TAgs Relationship) system that uses the notion of Normalized Image Tag Clarity (nitc) to find visual-representative tags . A visual-representative tag effectively describes the visual content of the images. Further, we visually demonstrate relationships between popular tags and visual-representative tags as well as co-occurrence likelihood of a pair of tags associated with a search tag or image using tag relationship graph (trg). We demonstrate various innovative features of i Avatar with a real-world dataset and show that it enriches users' understanding of various important tag features during image search.