Abstract: Methods and systems for improving precision of content matching systems at a platform are provided herein. Candidate matches for a media item are obtained. Each of the candidate matches indicates a reference media item including content that corresponds to content of the media item. Similarity data associated with the media item and the reference media items of the candidate matches is provided as input to a machine learning model. A determination is made, based on outputs of the model, of a content category associated with the media item and whether content of the media item matches content of a respective reference media item of the candidate matches in view of the determined content category. If so, action is taken to prevent users from the platform from accessing the content of the media item.

Abstract: Methods, systems, and media for analyzing spherical video content are provided. More particularly, methods, systems, and media for detecting two-dimensional videos placed on a sphere in abusive spherical video content by tiling the sphere are provided.

Abstract: Methods, systems, and media for analyzing spherical video content are provided. More particularly, methods, systems, and media for detecting two-dimensional videos placed on a sphere in abusive spherical video content by tiling the sphere are provided.

Abstract: Methods, systems, and media for analyzing spherical video content are provided. More particularly, methods, systems, and media for detecting two-dimensional videos placed on a sphere in abusive spherical video content by tiling the sphere are provided.

Abstract: Methods, systems, and media for analyzing spherical video content are provided. More particularly, methods, systems, and media for detecting two-dimensional videos placed on a sphere in abusive spherical video content by tiling the sphere are provided.

Abstract: An access policy module automatically applies an access policy to a video. Access policies frequently require manual review of an item to determine a proper access policy for the video, such as whether the video should be taken down, age-limited, or permitted general access. Results of a manual review of a video are stored along with the portion of the video that was manually reviewed and the access policy applied to the video. When a trigger event occurs indicating access policies should be considered for a video, the video is compared to reviewed portions of videos that were manually reviewed to determine if an access policy can be automatically applied with sufficient confidence. When insufficient confidence is reached or conflicting access policies both have high confidence, the video is scheduled for manual review with a priority level based on the possible access level of the video.