Video containment queries find the videos that have similar sequence of frames to query video clips. Applying sequence matching to all possible subsequences for video containment queries is computationally expensive for large volumes of video data. In this paper, we propose an efficient candidate segment selection scheme, which selects only a small set of subsequences to be matched to the query sequence, by using a cluster of similar frames, called a frame cluster. We also propose a new type of the ordinal feature, called a composite ordinal feature that allows multiple ranks to certain cells. In experiments with large scale video data sets, we show our method improves the query response time by efficiently selecting a set of subsequences for sequence matching.