Enhancing explainability of social recommendation using 2D graphs and word cloud visualizations

Saeed Amal, Mustafa Adam, Peter Brusilovsky, Einat Minkov, Tsvi Kuflik

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Explainability is an important desired property of recommendation systems. We consider a graph-based recommendation approach, which generates detailed explanations to users in the form of labelled connecting relational paths and present a visualization interface intended to convey such detailed relational information in clear and intuitive manner. As initial evaluation, we performed a user study at an academic conference, recommending participants the users may be interested to meet (using <u>rsr.cloud</u>). The feedbacks were enthusiastic, indicating that the proposed visualizations of relational explanations are engaging and useful.

Original languageEnglish
Title of host publicationProceedings of the 24th International Conference on Intelligent User Interfaces, IUI 2019
PublisherAssociation for Computing Machinery
Pages21-22
Number of pages2
ISBN (Electronic)9781450366731
DOIs
StatePublished - 16 Mar 2019
Event24th International Conference on Intelligent User Interfaces, IUI 2019 - Marina del Ray, United States
Duration: 16 Mar 201920 Mar 2019

Publication series

NameInternational Conference on Intelligent User Interfaces, Proceedings IUI

Conference

Conference24th International Conference on Intelligent User Interfaces, IUI 2019
Country/TerritoryUnited States
CityMarina del Ray
Period16/03/1920/03/19

Bibliographical note

Publisher Copyright:
© 2019 ACM.

Keywords

  • 2D graph
  • Visualized social recommendation
  • Word cloud

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction

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