Multimodal Graph-Based Event Detection And Summarization In Social Media Streams

The paper describes a multimodal graph-based system for addressing the Yahoo-Flickr Event Summarization Challenge of ACM Multimedia 2015. The objective is to automatically uncover structure within a collection of 100 million photos/videos in the form of detecting and identifying events, and summarizing them succinctly for consumer consumption. The presented system uses a sliding window over the stream of multimedia items to build and maintain a multimodal same-event image graph and applies a graph clustering algorithm to detect events. In addition, it makes use of a graph-based diversity-oriented ranking approach and a versatile event retrieval mechanism to access summarized instances of the events of interest. A demo of the system is online at http://mklab.iti.gr/acmmm2015-gc/.