Abstract: Examples are disclosed that relate to detecting cheating at a game platform level using machine learning techniques. One example provides a computing system comprising a logic subsystem and a data-holding subsystem. The data-holding subsystem comprises instructions executable by the logic subsystem to receive notifications related to user progress in a game provided by the game to the online game platform, apply a classifying function to classify the user progress in the game as normal or outlying based upon the notifications, if the progress is classified as outlying then taking an action in response to the outlying classification, and if the progress is not classified as outlying then not taking the action.

Abstract: The subject disclosure is directed towards a technology in which highlight (curated) videos are automatically generated for users to watch based upon estimated interest levels with respect to segments of a longer video or set of videos. In one aspect, statistics are collected with respect to actions of viewers of the video or set of videos. These may include playback-related actions such as the number of times a particular segment is played, and/or behavioral actions of viewers during the playback. Based upon which segments have the highest estimated interest levels, a subset of the segments are selected for a playback list, which when played provides the highlight/curated video.

Abstract: The subject disclosure is directed towards a technology in which highlight (curated) videos are automatically generated for users to watch based upon estimated interest levels with respect to segments of a longer video or set of videos. In one aspect, statistics are collected with respect to actions of viewers of the video or set of videos. These may include playback-related actions such as the number of times a particular segment is played, and/or behavioral actions of viewers during the playback. Based upon which segments have the highest estimated interest levels, a subset of the segments are selected for a playback list, which when played provides the highlight/curated video.

Abstract: The subject disclosure is directed towards a technology in which highlight (curated) videos are automatically generated for users to watch based upon estimated interest levels with respect to segments of a longer video or set of videos. In one aspect, statistics are collected with respect to actions of viewers of the video or set of videos. These may include playback-related actions such as the number of times a particular segment is played, and/or behavioral actions of viewers during the playback. Based upon which segments have the highest estimated interest levels, a subset of the segments are selected for a playback list, which when played provides the highlight/curated video.

Abstract: The subject disclosure is directed towards a technology in which highlight (curated) videos are automatically generated for users to watch based upon estimated interest levels with respect to segments of a longer video or set of videos. In one aspect, statistics are collected with respect to actions of viewers of the video or set of videos. These may include playback-related actions such as the number of times a particular segment is played, and/or behavioral actions of viewers during the playback. Based upon which segments have the highest estimated interest levels, a subset of the segments are selected for a playback list, which when played provides the highlight/curated video.