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

The effect of different set-based visualizations on user exploration of recommendations

Verbert, K and Parra, D and Brusilovsky, P (2014) The effect of different set-based visualizations on user exploration of recommendations. In: UNSPECIFIED.

Accepted Version
Available under License : See the attached license file.

Download (1MB)
[img] Plain Text (licence)
Available under License : See the attached license file.

Download (1kB)


When recommendations fail, trust in a recommender system often decreases, particularly when the system acts like a "black box". To deal with this issue, it is important to support exploration of recommendations by explicitly exposing relationships that can provide explanations. As an example, a graph-based visualization can help to explain collaborative filtering results by representing relationships among items and users. In our work, we focus on the use of visualization techniques to support exploration of multiple relevance prospects - such as relationships between different recommendation methods, socially connected users and tags. More specifically, we researched how users explore relationships between such multiple relevance prospects with two set-based visualization techniques: a clustermap and a Venn diagram. A comparative analysis of user studies with these two approaches indicates that, although effectiveness of recommendations increases with the use of a clustermap, the approach is too complex for a non-technical audience. A Venn diagram representation is more intuitive and users are more likely to explore relationships that help them find relevant items.


Social Networking:
Share |


Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
CreatorsEmailPitt UsernameORCID
Verbert, K
Parra, D
Brusilovsky, Ppeterb@pitt.eduPETERB0000-0002-1902-1464
Date: 1 January 2014
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Journal or Publication Title: CEUR Workshop Proceedings
Volume: 1253
Page Range: 37 - 44
Event Type: Conference
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISSN: 1613-0073
Date Deposited: 10 Aug 2015 16:01
Last Modified: 30 Mar 2021 15:55


Monthly Views for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item