Event-complementing Online Human Life Summarization based on Social Latent Semantic Analysis

Abstract

In this paper, online human life summarization is performed, based on multimedia content, published on social media. The life summaries are also automatically annotated with events, persons, places etc. Towards this direction, initially a content preparation module is activated that includes an intelligent wrapper. The content preparation module scans social networks, extracts their pages and segments them into tokens, in an unsupervised way. Next multimedia content is kept and it is associated to its respective metadata. In the following step, a novel ranking mechanism puts multimedia content in order of importance based on usercontent interactions. Finally the event-complementing summarization module produces a meaningful annotated video clip, based on a spectral visual clustering technique and the innovative Social Latent Semantic Analysis algorithm. Experimental results illustrate the promising performance of the proposed architecture and set some foundations for future research.