1. A computer-implemented method for determining category classifiers applicable to videos of a digital video repository, the method comprising: accessing a category-instance repository comprising relationships between categories and instances of categories, the category-instance repository derived from a corpus of documents comprising textual portions, the derivation comprising computing strengths for relationships between categories and instances based at least in part on frequencies of co-occurrence of the categories and instances over the corpus of documents; accessing a set of video concept classifiers derived from the videos and associated with concepts derived from textual metadata of the videos of the digital video repository; computing consistency scores for a plurality of the categories based at least in part on scores obtained from video concept classifiers associated with concepts corresponding to the instances of the plurality of categories; selectively removing categories of the category-instance repository based at least in part on whether the computed consistency scores indicate a threshold level of inconsistency; and determining, for each category of a plurality of the categories not removed, a category classifier based at least in part on the video concept classifiers of concepts associated with the category, the determined category classifier when applied to a video producing a score indicating whether the video represents the category for which the category classifier was determined.
1. A computer-implemented method for determining category classifiers applicable to videos of a digital video repository, the method comprising: accessing a category-instance repository comprising relationships between categories and instances of categories, the category-instance repository derived from a corpus of documents comprising textual portions, the derivation comprising computing strengths for relationships between categories and instances based at least in part on frequencies of co-occurrence of the categories and instances over the corpus of documents; accessing a set of video concept classifiers derived from the videos and associated with concepts derived from textual metadata of the videos of the digital video repository; computing consistency scores for a plurality of the categories based at least in part on scores obtained from video concept classifiers associated with concepts corresponding to the instances of the plurality of categories; selectively removing categories of the category-instance repository based at least in part on whether the computed consistency scores indicate a threshold level of inconsistency; and determining, for each category of a plurality of the categories not removed, a category classifier based at least in part on the video concept classifiers of concepts associated with the category, the determined category classifier when applied to a video producing a score indicating whether the video represents the category for which the category classifier was determined. 3. The computer-implemented method of claim 1 , wherein the consistency scores are median average deviation (MAD) scores computed from the scores obtained from the video concept classifiers.