Eliciting User Preferences for Personalized Explanations for Video Summaries

Oana Inel, Nava Tintarev, Lora Aroyo

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

3 Citations (Scopus)


Video summaries or highlights are a compelling alternative for exploring and contextualizing unprecedented amounts of video material. However, the summarization process is commonly automatic, non-transparent and potentially biased towards particular aspects depicted in the original video. Therefore, our aim is to help users like archivists or collection managers to quickly understand which summaries are the most representative for an original video. In this paper, we present empirical results on the utility of different types of visual explanations to achieve transparency for end users on how representative video summaries are, with respect to the original video. We consider four types of video summary explanations, which use in different ways the concepts extracted from the original video subtitles and the video stream, and their prominence. The explanations are generated to meet target user preferences and express different dimensions of transparency: concept prominence, semantic coverage, distance and quantity of coverage. In two user studies we evaluate the utility of the visual explanations for achieving transparency for end users. Our results show that explanations representing all of the dimensions have the highest utility for transparency, and consequently, for understanding the representativeness of video summaries.

Original languageEnglish
Title of host publicationUMAP '20: 28th ACM Conference on User Modeling, Adaptation and Personalization
Number of pages9
ISBN (Electronic)978-1-4503-6861-2
Publication statusPublished - 2020
Event28th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2020 - Genoa, Italy
Duration: 14 Jul 202017 Jul 2020


Conference28th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2020


  • user preferences
  • video summary representativeness
  • video summary transparency
  • visual explanation


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