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一种基于子空间学习的图像标签推荐方法
引用本文:祁 超. 一种基于子空间学习的图像标签推荐方法[J]. 计算机与现代化, 2016, 0(3): 68. DOI: 10.3969/j.issn.1006-2475.2016.03.014
作者姓名:祁 超
摘    要:

关 键 词:社会化标签  社会化图片  子空间学习  推荐系统  冷启动  
收稿时间:2016-03-17

An Approach of Image Tag Recommendation Based on Subspace Learning Model
QI Chao. An Approach of Image Tag Recommendation Based on Subspace Learning Model[J]. Computer and Modernization, 2016, 0(3): 68. DOI: 10.3969/j.issn.1006-2475.2016.03.014
Authors:QI Chao
Abstract:Represented by Flickr and Picasa, online photo albums allow users to tag images, hoping to make it more convenient as well as efficient to organize and retrieve image resources. Recently, automatic tag recommendation system has become a hot research field considering the increasing request that high-quality tags be provided. In this thesis, a new method for tag recommendation system is proposed. Unlike the traditional one which only depends on frequency information or visual feature similarity while neglecting the relation between visual content and the semantic meaning contained in tags thus leading to unsatisfactory recommendations, the new method can find out a latent subspace shared by visual features and tag contents using matrix factorization. As for an untagged image, recommendations can be made when its visual features are projected into the latent subspace and the relevance level it has with others tags is figured out. This new method has been proved efficient after being tested on NUS-WIDE data set with more satisfactory results.
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