Product Information Browsing Support System Using Analytic Hierarchy Process
Product Information Browsing Support System Using Analytic Hierarchy Process
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DOI：
10.1145/3486622.3493985
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发表时间：
2021-12
期刊：
影响因子：
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通讯作者：
Weijian Li;Masato Kikuchi;Tadachika Ozono
中科院分区：
文献类型：
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作者：
Weijian Li;Masato Kikuchi;Tadachika Ozono
大型电子商务网站可以收集和分析大量的用户偏好和行为，从而可以向用户推荐高度信任的产品。然而，对于个人或非企业团体来说，获得大规模的用户数据是非常困难的。因此，我们考虑是否可以利用决策领域的知识来获取用户偏好，并将其与基于内容的过滤相结合来设计信息检索系统。本研究描述了基于产品相似度和互联网上产品的多种其他视角构建高满意度产品信息浏览支持系统的过程。介绍了该系统的总体结构，并对其组成模块的工作原理进行了说明。最后，通过评价实验和问卷调查验证了系统的有效性。
Large-scale e-commerce sites can collect and analyze a large number of user preferences and behaviors, and thus can recommend highly trusted products to users. However, it is very difficult for individuals or non-corporate groups to obtain large-scale user data. Therefore, we consider whether knowledge of the decision-making domain can be used to obtain user preferences and combine it with content-based filtering to design an information retrieval system. This study describes the process of building a product information browsing support system with high satisfaction based on product similarity and multiple other perspectives about products on the Internet. We present the architecture of the proposed system and explain the working principle of its constituent modules. Finally, we demonstrate the effectiveness of the proposed system through an evaluation experiment and a questionnaire.