ACM Computing Surveys (CSUR)
SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries
IEEE Transactions on Pattern Analysis and Machine Intelligence
On Clustering Validation Techniques
Journal of Intelligent Information Systems
Robust and Efficient Cluster Analysis Using a Shared Near Neighbours Approach
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Content-based image retrieval by clustering
MIR '03 Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Hierarchical clustering of WWW image search results using visual, textual and link information
Proceedings of the 12th annual ACM international conference on Multimedia
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Pattern Recognition, Third Edition
Pattern Recognition, Third Edition
IGroup: presenting web image search results in semantic clusters
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Image retrieval on large-scale image databases
Proceedings of the 6th ACM international conference on Image and video retrieval
Clustering Using a Similarity Measure Based on Shared Near Neighbors
IEEE Transactions on Computers
Generating diverse and representative image search results for landmarks
Proceedings of the 17th international conference on World Wide Web
Unsupervised image-set clustering using an information theoretic framework
IEEE Transactions on Image Processing
Visual diversification of image search results
Proceedings of the 18th international conference on World wide web
Lightweight web image reranking
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Large Scale Tag Recommendation Using Different Image Representations
SAMT '09 Proceedings of the 4th International Conference on Semantic and Digital Media Technologies: Semantic Multimedia
Multimodal image retrieval over a large database
CLEF'09 Proceedings of the 10th international conference on Cross-language evaluation forum: multimedia experiments
Multi-source shared nearest neighbours for multi-modal image clustering
Multimedia Tools and Applications
Social media driven image retrieval
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Intelligent photo clustering with user interaction and distance metric learning
Pattern Recognition Letters
CASIS: a system for concept-aware social image search
Proceedings of the 21st international conference companion on World Wide Web
Community detection in Social Media
Data Mining and Knowledge Discovery
Hubness-Aware shared neighbor distances for high-dimensional k-nearest neighbor classification
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
A kernel-based framework for image collection exploration
Journal of Visual Languages and Computing
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Browsing and finding pictures in large-scale and heterogeneous collections is an important issue, most particularly for online photo sharing applications. Since such services are experiencing rapid growth of their databases, the tag-based indexing strategy and the results displayed in a traditional matrix representation may not be optimal for browsing and querying image collections. Naturally, unsupervised data clustering appeared as a good solution by presenting a summarized view of an image set instead of an exhaustive but useless list of its element. We present a new method for extracting meaningful and representative clusters based on a shared nearest neighbors (SNN) approach that treats both content-based features and textual descriptions (tags). We describe, discuss and evaluate the SNN method for image clustering and present some experimental results using the Flickr collections showing that our approach extracts representative information of an image set.