1. A computer-implemented method comprising: accessing a set of videos; determining degrees of similarity between pairs of the videos; for each video of a plurality of the videos, training a classifier for the video, the training comprising: forming, for the video, a training set comprising other ones of the videos based at least in part on the degrees of similarity; and training the classifier for the video based at least in part on audiovisual features extracted from the videos in the training set; applying the trained classifier for a first one of the videos to a second one of the videos to determine a degree of similarity between the second one of the videos and the first one of the videos; and responsive to the degree of similarity determined by applying the trained classifier being above a threshold value: based on the degree of similarity determined by applying the trained classifier, reducing cluster weights derived from user-supplied textual metadata of the first one of the videos, thereby obtaining first reduced cluster weight metadata; and associating the first reduced cluster weight metadata as metadata of the second one of the videos.