Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Enhancing recommendation diversity through a dual recommendation interface

Tsai, CH and Brusilovsky, P (2017) Enhancing recommendation diversity through a dual recommendation interface. In: UNSPECIFIED.

Available under License : See the attached license file.

Download (686kB) | Preview
[img] Plain Text (licence)
Available under License : See the attached license file.

Download (1kB)


The beyond-relevance objectives of recommender system are drawing more and more attention. For example, a diversity-enhanced interface has been shown to positively associate with overall levels of user satisfaction. However, little is known about how a diversity-enhanced interface can help users to accomplish various real-world tasks. In this paper, we present a visual diversity-enhanced interface that presents recommendations in a two-dimensional scatter plot. Our goal was to design a recommender system interface to explore the different relevance prospects of recommended items in parallel and to stress their diversity. A within-subject user study with real-life tasks was conducted to compare our visual interface to a standard ranked list interface. Our user study results show that the visual interface significantly reduced exploration efforts required for explored tasks. Also, the users' subjective evaluation shows significant improvement on many user-centric metrics. We show that the users explored a diverse set of recommended items while experiencing an improvement in overall user satisfaction.


Social Networking:
Share |


Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
CreatorsEmailPitt UsernameORCID
Tsai, CHcht77@pitt.eduCHT770000-0001-9188-0362
Brusilovsky, Ppeterb@pitt.eduPETERB0000-0002-1902-1464
Date: 1 January 2017
Date Type: Publication
Journal or Publication Title: CEUR Workshop Proceedings
Volume: 1884
Page Range: 10 - 15
Event Type: Conference
Schools and Programs: School of Computing and Information > Information Science
Refereed: Yes
ISSN: 1613-0073
Date Deposited: 31 Jul 2018 16:28
Last Modified: 03 Feb 2020 13:55


Monthly Views for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item