| 国内电子商务网站推荐系统信息服务质量比较研究——以淘宝、京东、亚马逊为例 |
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| 引用本文： | 洪亮,任秋圜,梁树贤.国内电子商务网站推荐系统信息服务质量比较研究——以淘宝、京东、亚马逊为例[J].图书情报工作,2016,60(23):97-110. |
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| 作者姓名： | 洪亮 任秋圜 梁树贤 |
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| 作者单位： | 1.武汉大学信息管理学院 武汉 430072;2.武汉大学信息资源研究中心 武汉 430072 |
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| 基金项目： | 本文系教育部人文社会科学重点研究基地重大项目“大数据资源的语义表示与组织研究——面向文化遗产领域”（项目编号：16JJD870002）和武汉大学人文社会科学青年学者学术发展计划学术团队项目研究成果之一。 |
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| 摘 要： | 目的/意义]推荐系统已经成为电子商务网站的重要组成部分之一，为用户提供多种形式的信息推荐服务。国内以淘宝、京东和亚马逊为代表的电子商务网站的推荐系统采用不同的技术架构和多种热点推荐技术，并且越来越重视信息服务的质量。对推荐系统服务质量进行比较研究，能够进一步推动电子商务推荐系统的发展。方法/过程]首先，从准确性、时效性、新颖性三个技术指标对比以上推荐系统的技术架构对于推荐服务质量的影响；其次，以用户体验作为信息服务质量评价的基础，对182名受访者进行热点技术的认可度调查，研究热点技术对推荐服务质量的影响；最后，对功能模块的用户体验情况进行调查和比较分析。结果/结论]在这些研究、调查和分析的基础上，给出电子商务推荐系统使用的技术架构和热点技术，以及改进功能模块设计的对策，以进一步提升推荐系统的信息服务质量。
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| 关 键 词： | 推荐系统 用户体验 电子商务 信息服务 |
| 收稿时间： | 2016-09-14 |
| 修稿时间： | 2016-11-17 |
A Comparative Study of Information Service Quality of E-commerce Sites' Recommender Systems-Take Taobao,Jingdong and Amazon as Examples |
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| Hong Liang,Ren Qiuyuan,Liang Shuxian.A Comparative Study of Information Service Quality of E-commerce Sites' Recommender Systems-Take Taobao,Jingdong and Amazon as Examples[J].Library and Information Service,2016,60(23):97-110. |
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| Authors: | Hong Liang Ren Qiuyuan Liang Shuxian |
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| Institution: | 1.School of Information Management, Wuhan University, Wuhan 430072;2.Center for the Studies of Information Resources, Wuhan University, Wuhan 430072 |
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| Abstract: | Purpose/significance] Recommender system has already been one of the most important parts of an e-commerce site and provides users with a variety of forms of information recommendation service.Nowadays, recommender systems in e-commerce sites such as Taobao, Jingdong and Amazon have adopted different frameworks and a variety of hotspot recommendation technologies,and paid more and more attention to quality of information service. Method/process] Therefore,firstly,we take the user experience as the basis for evaluating quality of information service and compare the influence of frameworks of the recommender systems mentioned above on the quality of recommendation service.Secondly, we study the research hotspots and the trend of the RecSys in recent 5 years, based on which we carry out an investigation of users' expectation and preference of these hotspots.Lastly, we conduct an evaluating experiment of user experience in e-commerce recommendation aiming at these e-commerce sites and make a comparative analysis. Result/conclusion] With the help of the research, investigation and experiment mentioned above, finally we come up with some strategies onhow to optimize the framework of recommender systems, pick up suitable hotspot recommendation technologies, and perfect the recommendation modules in e-commerce sites, all of which can apparently improve the quality of information service of e-commerce sites' recommender systems. |
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| Keywords: | recommender system user experience e-commerce information service |
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