Content Based Image Search for Clothing Recommendations in E-Commerce

Content Based Image Search for Clothing Recommendations in E-Commerce
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基于内容的电子商务服装推荐图像搜索

DOI:
10.1007/978-3-319-14998-1_11
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发表时间:
2015
期刊:
Multimedia Data Mining and Analytics
影响因子:
--
通讯作者:
Haoran Wang
Haoran Wang
中科院分区:
其他
文献类型:
--
作者:
Haoran Wang

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服装相似度的度量有很多算法 电子商务的建议。服装的相似性主要取决于它的形状,质地和风格。在本文中,我们介绍了三种模型定义的特征空间的服装推荐。的 基于草图的图像搜索主要集中于定义服装在轮廓维度上的相似性。采用空间特征袋方法进行测量 局部图像模式的服装相似性。最后,我们介绍了一个结合形状特征和标签的查询自适应形状模型 服装的语义信息。通过大量的仿真实验,验证了基于内容的图像搜索在服装推荐中的可行性和性能。
A number of algorithms exist in measuring clothing similarity for clothing recommendations in E-commerce. The clothing similarity mostly depends on its shape, texture and style. In this paper we introduce three models of defining feature space for clothing recommendations. The sketch-based image search mainly focuses on defining similarity of clothing in contour dimension. The spatial bag-of-feature approach is employed to measure the clothing similarity of local image patterns. Finally, we introduce a query adaptive shape model which combines shape characteristics and labels of clothing, in order to take the semantic information of clothing. A large number of simulations are given to show the feasibility and performance of the clothing recommendations by using content-based image search.
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