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The huge amount of videos currently available poses a difficult problem in semantic video retrieval. The success of query-by-concept, recently proposed to handle this problem, depends greatly on the accuracy of concept-based video indexing. This paper describes a multi-cue fusion approach toward improving the accuracy of semantic video indexing. This approach is based on a unified framework that explores and integrates both contextual correlation among concepts and temporal dependency amongdoi:10.1145/1459359.1459370 dblp:conf/mm/WengC08 fatcat:7xcrru23irbavnxhdb2afzdriy