Understanding Customers' Interests in the Wild

被引：1

作者：

Kang, Soowon ^{[1
]}

Kim, Auk ^{[2
]}

Lee, Jemin ^{[1
]}

Shin, Ikhee ^{[1
]}

Lee, Uichin ^{[3
]}

机构：

[1] Korea Adv Inst Sci & Technol, Grad Sch Knowledge Serv Engn, Daejeon, South Korea

[2] Chungnam Natl Univ, Dept Comp Sci & Engn, Daejeon, South Korea

[3] Korea Adv Inst Sci & Technol, Ind Engn & Management Res Inst, Daejeon, South Korea

来源：

PROCEEDINGS OF THE 2018 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING AND PROCEEDINGS OF THE 2018 ACM INTERNATIONAL SYMPOSIUM ON WEARABLE COMPUTERS (UBICOMP/ISWC'18 ADJUNCT) | 2018年

基金：

新加坡国家研究基金会;

关键词：

Customer interests;

D O I：

10.1145/3267305.3267625

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Today, retailers spend considerable efforts to provide a personalized shopping experience to their customers. As data-driven marketing helps to meet customer requirements, it is important to understand individual needs. However, offline stores-unlike their online counterparts-have great difficulty knowing their customers' needs due to a lack of proper context information. In this paper, we proposed a framework for estimating customer interests by using various sensor devices. The participants in our pilot study expected that recommendation services that adopt their interests would help to reduce their shopping time. As a result, shop assistants will have a stronger ability to understand, analyze, and even predict customer interests in the near future.

引用

页码：90 / 93

页数：4

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