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There are usually repetitive sub-segments in broadcast videos, which may be associated with high-level concepts or events, e.g., news footage, repeated scores in basketball. Unsupervised mining techniques provide generic solutions to discovering such temporal patterns in various video genres, which are currently the subject of great interests to researchers working on multimedia content analysis. In this paper, we propose a novel approach to automatically detecting repetitive patterns in adoi:10.1145/1101149.1101238 dblp:conf/mm/WangLY05 fatcat:lhri6pexzvh7jhjvbnbkcmth24