Abstract: A target tracking method is provided for a computer device. The method includes determining a target candidate region of a current image frame; capturing a target candidate image matching the target candidate region from the current image frame; determining a target region of the current image frame according to an image feature of the target candidate image; determining motion prediction data of a next image frame relative to the current image frame by using a motion prediction model and according to the image feature of the target candidate image; and determining a target candidate region of the next image frame according to the target region and the motion prediction data.

Abstract: The disclosure relates to an anti-collision structure for an engineering machine, the engineering machine has a tail frame arranged at a rear end. The anti-collision structure comprises an anti-collision body that at least partially covers side walls and a rear end wall of the tail frame, wherein the anti-collision body is made of plates and configured to have a streamline shape and a hollow structure. The anti-collision structure of the disclosure can effectively avoid collision to the rear end or tail of the engineering machine when the machine climbs or reverses, which improves the overall strength and impact-resistance of the tail frame and the main frame of the engineering machine. In addition, the three-dimensional streamlined shape of the anti-collision structure matches the whole vehicle in style, adding highlights for the electric driver. The disclosure also relates to an engineering machine comprising the anti-collision structure.

Abstract: A text query from a user may be received. Playlists associated with the text query may be identified. A relevance score may be calculated for each of the playlists based at least in part on a relevance of the corresponding playlist to the text query. Furthermore, content items may be identified where each of the content items is included in at least one of the playlists. For each of the identified content items, one or more playlists that includes the corresponding content item may be identified. A score for each of the content items may be calculated based on the relevance score for each of the playlists that includes the corresponding content item. Furthermore, a new playlist may be generated for the user based on the scores for each of the content items.

Abstract: Systems and techniques for suggesting media content contributions for a collaborative playlist are presented. The system can include a playlist component, a social component, and a suggestion component. The playlist component generates a playlist of media content in response to a request from a playlist owner. The social component invites at least one invitee to join a playlist collaboration group comprising the playlist owner and the at least one invitee. The suggestion component displays uploaded media content of the at least one invitee to allow the at least one invitee to add the uploaded media content to the playlist of the media content. The uploaded media content is determined based on a comparison of metadata of the uploaded media content with other metadata of the media content associated with the playlist.

Abstract: Systems and techniques for suggesting media content contributions for a collaborative playlist are presented. The system can include a playlist component, a social component, and a suggestion component. The playlist component generates a playlist of media content in response to a request from a playlist owner. The social component invites at least one invitee to join a playlist collaboration group comprising the playlist owner and the at least one invitee. The suggestion component displays uploaded media content of the at least one invitee to allow the at least one invitee to add the uploaded media content to the playlist of the media content. The uploaded media content is determined based on a comparison of metadata of the uploaded media content with other metadata of the media content associated with the playlist.

Abstract: Systems and techniques for suggesting media content contributions for a collaborative playlist are presented. The system can include a playlist component, a social component, and a suggestion component. The playlist component generates a playlist of media content in response to a request from a playlist owner. The social component invites at least one invitee to join a playlist collaboration group comprising the playlist owner and the at least one invitee. The suggestion component displays uploaded media content of the at least one invitee to allow the at least one invitee to add the uploaded media content to the playlist of the media content. The uploaded media content is determined based on a comparison of metadata of the uploaded media content with other metadata of the media content associated with the playlist.

Abstract: A text query from a user may be received. Playlists associated with the text query may be identified. A relevance score may be calculated for each of the playlists based at least in part on a relevance of the corresponding playlist to the text query. Furthermore, content items may be identified where each of the content items is included in at least one of the playlists. For each of the identified content items, one or more playlists that includes the corresponding content item may be identified. A score for each of the content items may be calculated based on the relevance score for each of the playlists that includes the corresponding content item. Furthermore, a new playlist may be generated for the user based on the scores for each of the content items.

Abstract: Systems and techniques for suggesting media content contributions for a collaborative playlist are presented. The system can include a playlist component, a social component, and a suggestion component. The playlist component generates a playlist of media content in response to a request from a playlist owner. The social component invites at least one invitee to join a playlist collaboration group comprising the playlist owner and the at least one invitee. The suggestion component displays uploaded media content of the at least one invitee to allow the at least one invitee to add the uploaded media content to the playlist of the media content. The uploaded media content is determined based on a comparison of metadata of the uploaded media content with other metadata of the media content associated with the playlist.

Abstract: This disclosure relates to screening potentially inappropriate online content. A flag is received that indicates online content is potentially inappropriate. The flag is generated by a source, such as a user, or a content classifier. The potential accuracy of the flag is determined or inferred based on a variety of factors, including a reputation of the source, and the flag is categorized as requiring higher priority administrative action or requiring lower priority administrative action based in part on the potential accuracy of the flag. In addition, administrative action is taken based in part on the categorization of the flag.