Modern Information Retrieval
Distortion Invariant Object Recognition in the Dynamic Link Architecture
IEEE Transactions on Computers
Introduction to Stochastic Search and Optimization
Introduction to Stochastic Search and Optimization
Automatic image annotation and retrieval using cross-media relevance models
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Recognition with Local Features: the Kernel Recipe
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Convex Optimization
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Image annotations by combining multiple evidence & wordNet
Proceedings of the 13th annual ACM international conference on Multimedia
HT06, tagging paper, taxonomy, Flickr, academic article, to read
Proceedings of the seventeenth conference on Hypertext and hypermedia
Image annotation refinement using random walk with restarts
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Toward bridging the annotation-retrieval gap in image search by a generative modeling approach
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
The Google Similarity Distance
IEEE Transactions on Knowledge and Data Engineering
Flickr tag recommendation based on collective knowledge
Proceedings of the 17th international conference on World Wide Web
Learning to reduce the semantic gap in web image retrieval and annotation
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Near-duplicate keyframe retrieval by nonrigid image matching
MM '08 Proceedings of the 16th ACM international conference on Multimedia
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Cross-media manifold learning for image retrieval & annotation
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Learning tag relevance by neighbor voting for social image retrieval
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Proceedings of the 18th international conference on World wide web
Proceedings of the 18th international conference on World wide web
Distance metric learning from uncertain side information with application to automated photo tagging
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Tag quality improvement for social images
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Sequential greedy approximation for certain convex optimization problems
IEEE Transactions on Information Theory
Context seeking with social tags
Proceedings of the fourth workshop on Exploiting semantic annotations in information retrieval
Mining tweets for tag recommendation on social media
Proceedings of the 3rd international workshop on Search and mining user-generated contents
Context-aware image semantic extraction in the social web
Proceedings of the 21st international conference companion on World Wide Web
Tag ranking by propagating relevance over tag and image graphs
Proceedings of the 4th International Conference on Internet Multimedia Computing and Service
Online multi-modal distance learning for scalable multimedia retrieval
Proceedings of the sixth ACM international conference on Web search and data mining
Topic based photo set retrieval using user annotated tags
Multimedia Tools and Applications
Adaptive all-season image tag ranking by saliency-driven image pre-classification
Journal of Visual Communication and Image Representation
Semantic context based refinement for news video annotation
Multimedia Tools and Applications
Hi-index | 0.00 |
Tags of social images play a central role for text-based social image retrieval and browsing tasks. However, the original tags annotated by web users could be noisy, irrelevant, and often incomplete for describing the image contents, which may severely deteriorate the performance of text-based image retrieval models. In this paper, we aim to overcome the challenge of social tag ranking for a corpus of social images with rich user-generated tags by proposing a novel two-view learning approach. It can effectively exploit both textual and visual contents of social images to discover the complicated relationship between tags and images. Unlike the conventional learning approaches that usually assume some parametric models, our method is completely data-driven and makes no assumption of the underlying models, making the proposed solution practically more effective. We formally formulate our method as an optimization task and present an efficient algorithm to solve it. To evaluate the efficacy of our method, we conducted an extensive set of experiments by applying our technique to both text-based social image retrieval and automatic image annotation tasks, in which encouraging results showed that the proposed method is more effective than the conventional approaches.