Abstract: Described are computer-based methods and apparatuses, including computer program products, for defining video advertising channels. A set of requirements is received for an advertising channel. A training set of video content is identified based on the set of requirements. A set of baseline categorizations is received that includes, for each video in the training set of video content, a categorization for each requirement from the set of requirements. A set of experiments is calculated based on the training set of video content and the set of baseline categorizations to determine video content for the advertising channel.

Abstract: Systems and methods for automatically matching in real-time an advertisement with a video desired to be viewed by a user are provided. A database is created that stores one or more attributes (e.g., visual metadata relating to objects, faces, scene classifications, pornography detection, scene segmentation, production quality, fingerprinting) associated with a plurality of videos. Supervised machine learning can be used to create signatures that uniquely identify particular attributes of interest, which can then be used to generate the attributes associated with the plurality of videos. When a user requests to view an on-line video having associated with it an advertisement, an advertisement can be selected for display with the video based on matching an advertiser's requirements or campaign parameters with the stored attributes associated with the requested video, with the user's information, or a combination thereof.