Query based event extraction along a timeline
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Hot Topic Extraction Based on Timeline Analysis and Multidimensional Sentence Modeling
IEEE Transactions on Knowledge and Data Engineering
Comparison of multiepisode video summarization algorithms
EURASIP Journal on Applied Signal Processing
Topical summarization of web videos by visual-text time-dependent alignment
Proceedings of the international conference on Multimedia
Trains of thought: generating information maps
Proceedings of the 21st international conference on World Wide Web
Modeling topic trends on the social web using temporal signatures
Proceedings of the twelfth international workshop on Web information and data management
An effective multi-clue fusion approach for web video topic detection
Proceedings of the 20th ACM international conference on Multimedia
Proceedings of the 21st ACM international conference on Information and knowledge management
| Hi-index | 0.00 |
As the amount of social media shared on the Internet grows increasingly, it becomes possible to explore a topic with a novel, people based viewpoint. Contrasting with traditional man-made topic summarization which provide the personal view of its author, we want to focus on public reaction to events. To this end, we propose an approach to automatically generate a timeline of popular events related to a given topic. Time segments of interest are extracted from Google Trends results using a simple statistical approach. Each event, relevant to the specified topic, is illustrated on a timeline by videos mined from social media sharing platforms that gives context to the events and offers an overview of what has caught people's attention. We report the results provided by our approach for automatically illustrating the popular moments of four celebrities.