SIA OpenIR  > 机器人学研究室
User-curated image collections: Modeling and recommendation
Li, Yuncheng; Mei T(梅涛); Cong Y(丛杨); Luo JB(罗杰波)
Department机器人学研究室
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
PublisherIEEE
Publication PlacePiscataway, NJ, USA
2015
Pages591-600
Indexed ByEI ; CPCI(ISTP)
EI Accession number20161702280775
WOS IDWOS:000380404600072
Contribution Rank3
ISBN978-1-4799-9925-5
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.
Language英语
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/18519
Collection机器人学研究室
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.
Files in This Item:
File Name/Size DocType Version Access License
User-curated image c(1100KB)会议论文 开放获取CC BY-NC-SAView Application Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Li, Yuncheng]'s Articles
[Mei T(梅涛)]'s Articles
[Cong Y(丛杨)]'s Articles
Baidu academic
Similar articles in Baidu academic
[Li, Yuncheng]'s Articles
[Mei T(梅涛)]'s Articles
[Cong Y(丛杨)]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Li, Yuncheng]'s Articles
[Mei T(梅涛)]'s Articles
[Cong Y(丛杨)]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: User-curated image collections.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.