iAVATAR: an interactive tool for finding and visualizing visual-representative tags in image search

Authors:
Aixin Sun;Sourav S. Bhowmick;Yao Liu
Affiliations:
Nanyang Technological University, Singapore;Nanyang Technological University, Singapore;Nanyang Technological University, Singapore
Venue:
Proceedings of the VLDB Endowment
Year:
2010

Citing 8
Cited 0

Predicting query performance

SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Distinctive Image Features from Scale-Invariant Keypoints

International Journal of Computer Vision
World explorer: visualizing aggregate data from unstructured text in geo-referenced collections

Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
Visualizing tags over time

ACM Transactions on the Web (TWEB)
Topigraphy: visualization for large-scale tag clouds

Proceedings of the 17th international conference on World Wide Web
Retrieval and feedback models for blog feed search

Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Image tag clarity: in search of visual-representative tags for social images

WSM '09 Proceedings of the first SIGMM workshop on Social media
NUS-WIDE: a real-world web image database from National University of Singapore

Proceedings of the ACM International Conference on Image and Video Retrieval

Quantified Score

Hi-index	0.00

Visualization

Abstract

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 iAvatar (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 iAvatar with a real-world dataset and show that it enriches users' understanding of various important tag features during image search.