数字图书馆论坛Issue(10)：30-36,7.DOI:10.3772/j.issn.1673-2286.2019.10.005
从用户视角理解智能推荐系统
Understanding Recommender Systems from Users’ Perspective
摘要
Abstract
In order to solve the problems of information overload and information anxiety, recommendation system have been applied widely in many different areas. In order to effectively solve these problems, it is necessary to understand how users perceive recommendation systems and what factors affect their perceptions of usefulness and effectiveness of recommendations. This is very necessary in order to design and evaluate systems. This research is an inductive exploratory pilot study that aims to give a first indication towards understanding what type of factors influence these perceptions. Data was collected through one focus group interview and was then coded using content analysis supported by NVivo 11. The findings of the study reveal that users’ preference, users’ behaviors and business characteristics are 3 criteria which interviewees perceived as important evidence of recommendation. Moreover, interviewees expressed that the factors which affects their perceptions of usefulness and effectiveness of recommendations are perceived interaction effort, diversity of recommendation results, coverage, perceived usefulness, contextual compatibility, perceived controllability, flexibility, cross-platform data sharing, accuracy, novelty, and transparency. This study is not generalizable due to the small numbers of respondents, but provides an initial informed emergent theory that can help designers and developers of recommendation systems improve their efforts.关键词
推荐系统/用户感知/质性研究/感知因素Key words
Recommendation Systems/User Perception/Qualitative Study/Impact Factor Study分类
社会科学引用本文复制引用
罗婷予,Miguel Baptista Nunes..从用户视角理解智能推荐系统[J].数字图书馆论坛,2019,(10):30-36,7.基金项目
本研究得到广东省自然科学基金面上项目"基于人工智能的虚拟现实古籍理论与模型研究"(编号:2019A1515011260)以及中山大学信息科学、信息管理和信息系统学科交叉的培育研究科研启动经费(经费号:20000-18841200)资助. （编号:2019A1515011260）
