The use of MMR, diversity-based reranking for reordering documents and producing summaries
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
A unified framework for semantics and feature based relevance feedback in image retrieval systems
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Unifying Keywords and Visual Contents in Image Retrieval
IEEE MultiMedia
Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
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
Automatic multimedia cross-modal correlation discovery
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Multimodal concept-dependent active learning for image retrieval
Proceedings of the 12th annual ACM international conference on Multimedia
Improving recommendation lists through topic diversification
WWW '05 Proceedings of the 14th international conference on World Wide Web
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Improving web search results using affinity graph
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Relevance feedback using adaptive clustering for image similarity retrieval
Journal of Systems and Software
Two-scale image retrieval with significant meta-information feedback
Proceedings of the 13th annual ACM international conference on Multimedia
Diversifying image search with user generated content
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Visual diversification of image search results
Proceedings of the 18th international conference on World wide web
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
What Else Is There? Search Diversity Examined
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Overview of the ImageCLEFphoto 2008 photographic retrieval task
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
A hybrid unsupervised image re-ranking approach with latent topic contents
Proceedings of the ACM International Conference on Image and Video Retrieval
Defining the dynamicity and diversity of text collections
ECDL'10 Proceedings of the 14th European conference on Research and advanced technology for digital libraries
Multi-dimensional search result diversification
Proceedings of the fourth ACM international conference on Web search and data mining
Visual topic model for web image annotation
ICIMCS '10 Proceedings of the Second International Conference on Internet Multimedia Computing and Service
MM '11 Proceedings of the 19th ACM international conference on Multimedia
A non-parametric visual-sense model of images--extending the cluster hypothesis beyond text
Multimedia Tools and Applications
Social image search with diverse relevance ranking
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
Explicit diversification of image search
Proceedings of the 3rd ACM conference on International conference on multimedia retrieval
Multimedia search reranking: A literature survey
ACM Computing Surveys (CSUR)
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In the area of image retrieval, post-retrieval processing is often used to refine the retrieval results to better satisfy users' requirements. Previous methods mainly focus on presenting users with relevant results. However, in most cases, users cannot clearly present their requirements by several query words. Therefore, relevant results with rich topic coverage are more likely to meet users' ambiguous needs. In this paper, a re-ranking method based on topic richness analysis is proposed to enrich topic coverage in retrieval results. Furthermore, a quantitative criterion called diversity scores (DS) is proposed to evaluate the improvement. Given a set of images, topics that are rarely included in the set are scarce topics, as oppose to rich topics that are widely distributed among the set. Scarce topics contribute more than rich topics do to the DS of images. Five researchers are invited to evaluate the re-ranked results both in topic coverage and relevance. Experimental results on over 20,000 images demonstrate that our proposed approach is effective in improving the topic coverage of retrieval results without loss of relevance.