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User-curated image collections: Modeling and recommendation
Li, Yuncheng; Mei T(梅涛); Cong Y(丛杨); Luo JB(罗杰波)
Conference Name3rd IEEE International Conference on Big Data, IEEE Big Data 2015
Conference DateOctober 29-November 1, 2015
Conference PlaceSanta Clara, CA, United states
Source PublicationProceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015
Publication PlacePiscataway, NJ, USA
Indexed ByEI ; CPCI(ISTP)
EI Accession number20161702280775
WOS IDWOS:000380404600072
Contribution Rank3
KeywordImage Collection Similarity Measure Visual Features Sparse Representation Metric Learning
AbstractMost state-of-the-art image retrieval and recommendation systems predominantly focus on individual images. In contrast, socially curated image collections, condensing distinctive yet coherent images into one set, are largely overlooked by the research communities. In this paper, we aim to design a novel recommendation system that can provide users with image collections relevant to individual personal preferences and interests. To this end, two key issues need to be addressed, i.e., image collection modeling and similarity measurement. For image collection modeling, we consider each image collection as a whole in a group sparse reconstruction framework and extract concise collection descriptors given the pretrained dictionaries. We then consider image collection recommendation as a dynamic similarity measurement problem in response to user's clicked image set, and employ a metric learner to measure the similarity between the image collection and the clicked image set. As there is no previous work directly comparable to this study, we implement several competitive baselines and related methods for comparison. The evaluations on a large scale Pinterest data set have validated the effectiveness of our proposed methods for modeling and recommending image collections.
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Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type会议论文
Corresponding AuthorLi, Yuncheng
Affiliation1.University of Rochester, Department of Computer Science, Rochester, NY, United States
2.Microsoft Research, Building 2, No. 5 Dan Ling Street, Haidian District, Beijing, China
3.Chinese Academy of Sciences, Shenyang Institute of Automation, State Key Laboratory of Robotics, China
Recommended Citation
GB/T 7714
Li, Yuncheng,Mei T,Cong Y,et al. User-curated image collections: Modeling and recommendation[C]. Piscataway, NJ, USA:IEEE,2015:591-600.
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