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| Content Provider | ACM Digital Library |
|---|---|
| Author | Choi, Jaeyoung Kim, Eungchan Friedland, Gerald Larson, Martha Hanjalic, Alan |
| Abstract | We present Evento 360 (URL: http://evento360.info), an online interactive social event browser, which allows the user to explore events detected within a web-scale multimedia corpus. The system addresses five key aspects of social multimedia event detection and summarization: multimodality, scale, diversity of representations, noise of multimedia items, and missing metadata. The detection algorithm uses unsupervised clustering approach that exploits temporal, spatial and textual metadata. For each detected event cluster, to choose the best subset of photos that meet both relevance and diversity criteria, the system uses hierarchical clustering that exploits both visual and audio information. Evento 360's user interface provides a search feature that is not limited to a certain set of events, but rather can handle an arbitrary event query. It allows the user to retrieve and explore relevant events. The system scales well and is effective in producing high-quality summaries of the detected events. |
| Starting Page | 193 |
| Ending Page | 196 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781450334594 |
| DOI | 10.1145/2733373.2809934 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2015-10-13 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Topic models Social event detection Event summarization |
| Content Type | Text |
| Resource Type | Article |
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