How to Recommend? User Trust Factors in Movie Recommender Systems

被引：48

作者：

Berkovsky, Shlomo ^{[1
]}

Taib, Ronnie ^{[1
]}

Conway, Dan ^{[1
]}

机构：

[1] CSIRO, Data6l, Canberra, ACT, Australia

来源：

IUI'17: PROCEEDINGS OF THE 22ND INTERNATIONAL CONFERENCE ON INTELLIGENT USER INTERFACES | 2017年

关键词：

Recommender systems; user-system trust; presentation of recommendations; user study; SELF-CONFIDENCE; AUTOMATION; MANAGEMENT;

D O I：

10.1145/3025171.3025209

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

How much trust a user places in a recommender is crucial to the uptake of the recommendations. Although prior work established various factors that build and sustain user trust, their comparative impact has not been studied in depth. This paper presents the results of a crowd-sourced study examining the impact of various recommendation interfaces and content selection strategies on user trust. It evaluates the subjective ranking of nine key factors of trust grouped into three dimensions and examines the differences observed with respect to users' personality traits.

引用

页码：287 / 300

页数：14

共 43 条

[1] [Anonymous], 2011, P 5 ACM C RECOMMENDE
[2] [Anonymous], J ASS INFORM SYSTEMS
[3] [Anonymous], 2015, RECOMMENDER SYSTEMS
[4] [Anonymous], P WORKSH PERS REC SY
[5] [Anonymous], 2005, P 10 INT C INT US IN, DOI DOI 10.1145/1040830.1040870
[6] [Anonymous], P INT C INT US INT I
[7] [Anonymous], 2022, Recommender Systems Handbook, DOI DOI 10.1007/978-1-0716-2197-415
[8] [Anonymous], 2015, RECOMMENDER SYSTEMS
[9] CONTROLLING THE FALSE DISCOVERY RATE - A PRACTICAL AND POWERFUL APPROACH TO MULTIPLE TESTING
BENJAMINI, Y
HOCHBERG, Y
[J]. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 1995, 57 (01) : 289 - 300
[10] Design of Experiments With Multiple Independent Variables: A Resource Management Perspective on Complete and Reduced Factorial Designs
Collins, Linda M.
Dziak, John J.
Li, Runze
[J]. PSYCHOLOGICAL METHODS, 2009, 14 (03) : 202 - 224

← 1 2 3 4 5 →