Knowledge-based configuration of videos using feature models.

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem KonferenzbandBegutachtung

Abstract

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.
Originalspracheenglisch
Titel26th ACM International Systems and Software Product Line Conference, SPLC 2022 - Proceedings
Redakteure/-innenAlexander 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
Herausgeber (Verlag)Association of Computing Machinery
Seiten188-192
Seitenumfang5
BandB
ISBN (elektronisch)9781450392068
DOIs
PublikationsstatusVeröffentlicht - 12 Sept. 2022

ASJC Scopus subject areas

  • Software

Fingerprint

Untersuchen Sie die Forschungsthemen von „Knowledge-based configuration of videos using feature models.“. Zusammen bilden sie einen einzigartigen Fingerprint.

Dieses zitieren