A tutorial on support vector regression
Statistics and Computing
Natural color image enhancement and evaluation algorithm based on human visual system
Computer Vision and Image Understanding
The Design of High-Level Features for Photo Quality Assessment
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Video search reranking via information bottleneck principle
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Aesthetic Primitives of Images for Visualization
IV '07 Proceedings of the 11th International Conference Information Visualization
Pagerank for product image search
Proceedings of the 17th international conference on World Wide Web
Photo and Video Quality Evaluation: Focusing on the Subject
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Ranking and classifying attractiveness of photos in folksonomies
Proceedings of the 18th international conference on World wide web
OpinionMiner: a novel machine learning system for web opinion mining and extraction
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
The role of tags and image aesthetics in social image search
WSM '09 Proceedings of the first SIGMM workshop on Social media
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Visual query suggestion: Towards capturing user intent in internet image search
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Personalized photograph ranking and selection system
Proceedings of the international conference on Multimedia
Supervised reranking for web image search
Proceedings of the international conference on Multimedia
Prediction of favourite photos using social, visual, and textual signals
Proceedings of the international conference on Multimedia
Training data collection system for a learning-based photographic aesthetic quality inference engine
Proceedings of the international conference on Multimedia
Automatic image semantic interpretation using social action and tagging data
Multimedia Tools and Applications
Learning to re-rank: query-dependent image re-ranking using click data
Proceedings of the 20th international conference on World wide web
Aspect ranking: identifying important product aspects from online consumer reviews
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Studying aesthetics in photographic images using a computational approach
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Topic-driven reader comments summarization
Proceedings of the 21st ACM international conference on Information and knowledge management
Can social features help learning to rank youtube videos?
WISE'12 Proceedings of the 13th international conference on Web Information Systems Engineering
Fashion-focused creative commons social dataset
Proceedings of the 4th ACM Multimedia Systems Conference
Opinion-based User Profile Modeling for Contextual Suggestions
Proceedings of the 2013 Conference on the Theory of Information Retrieval
Rare is interesting: connecting spatio-temporal behavior patterns with subjective image appeal
Proceedings of the 2nd ACM international workshop on Geotagging and its applications in multimedia
Synesthetic enrichment of mobile photography
Proceedings of the 2013 ACM international workshop on Immersive media experiences
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The increasing number of images available online has created a growing need for efficient ways to search for relevant content. Text-based query search is the most common approach to retrieve images from the Web. In this approach, the similarity between the input query and the metadata of images is used to find relevant information. However, as the amount of available images grows, the number of relevant images also increases, all of them sharing very similar metadata but differing in other visual characteristics. This paper studies the influence of visual aesthetic quality in search results as a complementary attribute to relevance. By considering aesthetics, a new ranking parameter is introduced aimed at improving the quality at the top ranks when large amounts of relevant results exist. Two strategies for aesthetic rating inference are proposed: one based on visual content, another based on the analysis of user comments to detect opinions about the quality of images. The results of a user study with $58$ participants show that the comment-based aesthetic predictor outperforms the visual content-based strategy, and reveals that aesthetic-aware rankings are preferred by users searching for photographs on the Web.