An automatic event-complementing human life summarization scheme based on a social computing method over social media content

This paper proposes a human life summarization scheme based on multimedia content published on social media. In this context the term “life” includes the events, occasions and activities users post on their walls. Towards this direction, an innovative architecture is designed that consists of two modules: the content preparation and the content summarization module. During content preparation, a Social Media web page is automatically segmented into tokens. Next multimedia content is kept and it is associated to its respective metadata (date of post, events, likes, persons, comments etc.) after filtering information through the YAGO2 knowledge base. Then a novel ranking mechanism puts multimedia content in order of importance based on a social computing methodology. Finally the summarization module produces a meaningful video clip that includes the top moments of one’s life without completely disregarding the less important. To the best of the authors’ knowledge, this is one of the first human life summarization schemes that are based on social media content. Experimental results illustrate the promising performance of the proposed architecture and set a basis for future research. © 2015, Springer Science+Business Media New York