Knowledge-based configuration of videos using feature models.

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


User-centricity and variability play an increasingly important role in various application domains. A trend in the context of creating and sharing videos is to personalize contents and related navigation features. Such a personalization is needed to be able to take into account the preferences of users in terms of preferred contents, existing knowledge levels (e.g., in the context of teaching videos), and available time for watching a video. In this paper, we present an approach to define variability properties of videos. In this context, we show how the different modeling concepts of feature models can be used to represent variability properties of videos and also discuss related open research challenges.
Original languageEnglish
Title of host publication26th ACM International Systems and Software Product Line Conference, SPLC 2022 - Proceedings
EditorsAlexander Felfernig, Lidia Fuentes, Jane Cleland-Huang, Wesley K.G. Assuncao, Wesley K.G. Assuncao, Clement Quinton, Jianmei Guo, Klaus Schmid, Marianne Huchard, Inmaculada Ayala, Jose Miguel Rojas, Viet-Man Le, Jose Miguel Horcas
PublisherAssociation of Computing Machinery
Number of pages5
ISBN (Electronic)9781450392068
Publication statusPublished - 12 Sept 2022


  • configuration
  • feature models
  • interactive video
  • learning effectiveness
  • personalized video
  • video summarizing

ASJC Scopus subject areas

  • Software

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