Abstract
Due to the rapidly increasing video data on the Web, much research effort has been devoted to develop video retrieval methods which can efficiently retrieve videos of interest. Considering the limited man-power, it is much expected to develop retrieval methods which use features automatically extracted from videos. However, since features only represent physical contents (e.g. color, edge, motion, etc.), retrieval methods require knowledge of how to use/integrate features for retrieving videos relevant to queries. To obtain such knowledge, this thesis concentrates on 'video data mining' where videos are analyzed using data mining techniques which extract previously unknown, interesting patterns in underlying data. Thereby, patterns for retrieving relevant shots to queries are extracted as explicit knowledge.
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