A probabilistic model for retrospective news event detection
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Video booklet: a natural video searching and browsing interface
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
Modeling personal and social network context for event annotation in images
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
Automatic creation of photo books from stories in social media
Proceedings of second ACM SIGMM workshop on Social media
Finding media illustrating events
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Analysing Facebook features to support event detection for photo-based Facebook applications
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
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With the large amount of photos and other media items that are added daily to social media sites, it has become very hard for the user to identify the photos of a specific event, especially as it can be spread over a lot of users and albums. Additionally, people may have different definitions of what they see as an event, and in many cases this definition can change over time. In this paper we propose a method to enable users to easily browse photos in an event-oriented way. We exploit a probabilistic approach that performs the heavy computation offline, but flexibly leaves the definition of the event to the user in the online time. In our approach the user starts by an initial small set of photos which are related to an event or several events in her opinion, and retrieves the photos that are highly probable to belong to the same event. The user can interactively change this initial set based on the newly retrieved photos.