Eliciting User Preferences for Personalized Explanations for Video Summaries

Conference Paper (2020)
Author(s)

Oana Inel (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Nava Tintarev (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Lora Aroyo

Research Group
Web Information Systems
DOI related publication
https://doi.org/10.1145/3340631.3394862 Final published version
More Info
expand_more
Publication Year
2020
Language
English
Research Group
Web Information Systems
Pages (from-to)
98-106
ISBN (electronic)
978-1-4503-6861-2
Event
28th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2020 (2020-07-14 - 2020-07-17), Genoa, Italy
Downloads counter
127

Abstract

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.