Optimizing item and subgroup configurations for social-aware VR shopping
Optimizing item and subgroup configurations for social-aware VR shopping
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DOI：
10.14778/3389133.3389143
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发表时间：
2020-02
影响因子：
2.5
通讯作者：
Shao-Heng Ko;Hsu-Chao Lai;Hong-Han Shuai;De-Nian Yang;Wang-Chien Lee;Philip S. Yu
中科院分区：
文献类型：
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作者：
Shao-Heng Ko;Hsu-Chao Lai;Hong-Han Shuai;De-Nian Yang;Wang-Chien Lee;Philip S. Yu
在VR购物中心购物被认为是电子商务的一个范式转变，但大多数传统的VR购物平台都是为单一用户设计的。在本文中，我们设想了一个VR团购场景，它比传统的实体店团购和网络购物带来了主要优势：1）配置灵活的商品展示和子群体划分，以满足群体中的个人兴趣，2）支持子群体中的社交互动，以促进销售。因此，我们制定了社交感知VR群组项目配置（SVGIC）问题，为VR群组购物中灵活分区的用户子组配置一组显示项目。我们证明了SVGIC是APX-困难的，也是NP-困难的近似[方程]。我们设计了一个4-近似算法的基础上的想法，共同显示子组形成（CSF）配置适当的项目显示给不同的朋友。在真实的VR数据集上的实验结果和使用hTC VIVE的用户研究表明，我们的算法优于基线方法至少30.1%的解决方案质量。
Shopping in VR malls has been regarded as a paradigm shift for E-commerce, but most of the conventional VR shopping platforms are designed for a single user. In this paper, we envisage a scenario of VR group shopping, which brings major advantages over conventional group shopping in brick-and-mortar stores and Web shopping: 1) configure flexible display of items and partitioning of subgroups to address individual interests in the group, and 2) support social interactions in the subgroups to boost sales. Accordingly, we formulate the Social-aware VR Group-Item Configuration (SVGIC) problem to configure a set of displayed items for flexibly partitioned subgroups of users in VR group shopping. We prove SVGIC is APX-hard and also NP-hard to approximate within [EQUATION]. We design a 4-approximation algorithm based on the idea of Co-display Subgroup Formation (CSF) to configure proper items for display to different subgroups of friends. Experimental results on real VR datasets and a user study with hTC VIVE manifest that our algorithms outperform baseline approaches by at least 30.1% of solution quality.