Content selection criteria for news multi-video summarization based on human strategies

• Published in: International journal on digital libraries Vol. 22; no. 1; pp. 1 - 14
• Main Authors: Barbieri, Tamires Tessarolli de Souza, Goularte, Rudinei
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2021; Springer Nature B.V
• Subjects: Computer Science; Criteria; Database Management; Information overload; Information Systems and Communication Service; Multimedia; News; Semantics; Video data; Multimedia; Multi-video summarization; Digital video; Human strategies
• ISSN: 1432-5012; 1432-1300
• DOI: 10.1007/s00799-020-00281-9

In the recent years, the multimedia data volume produced and available for access has increased continuously and quickly, notably video content. This context has also increased the overload information problem: finding content of interest in the huge amount of available options. So, efficient schemes for content access are needed. Automatic video summarization is a research field that deals with this problem. Furthermore, the current multimedia systems make available several videos related to the same topic but having, each one, a piece of unique complementary information. This fact highlights the need for multi-video summarization to deal with users’ interest in being informed about a subject from a set of videos without being obligated to watch the whole set. However, the literature analysis shows that human strategies are not considered to define criteria used to automatically select video segments that will compose a summary and the focus of techniques has been the identification of common information in different videos. In this work, we investigate human strategies for news multi-video summarization. The results of the study with real users uncover relevant criteria to develop summaries, with potential to increase their semantics and bring them closer to users’ perception.