Abstract: This application discloses a method for determining an implantation location of recommendation information performed at a computer device. The method includes: acquiring a target video; acquiring, according to a scene change status of the target video, a target video frame being used for location detection; performing image recognition on the target video frame to obtain masking information of the target video frame including a first region of an object of a target type in the target video frame; and determining an implantation location of recommendation information in the target video frame based on the first region. Image recognition processing is performed on the target video frame to obtain the masking information of the target video frame, so as to determine the implantation location in the target video frame on the basis of the first region corresponding to the object of the target type in the target video frame.

Abstract: A method for detecting an information insertion region is provided. In the method, a video is obtained. The video is segmented to obtain video fragments, each of the video fragments including a subset of image frames in the video. A target frame is obtained in the video fragments. Objects in the target frame are identified and segmented, to obtain labeling information corresponding to the objects. A target object is determined according to the labeling information. Clustering is performed on the target object, to obtain a plurality of candidate to-be-inserted regions. A target candidate to-be-inserted region is determined from the candidate to-be-inserted regions. Further, maximum rectangle searching is performed in the target candidate to-be-inserted region to obtain a target to-be-inserted region in which an image is to be inserted.

Abstract: This application discloses a method for determining an implantation location of recommendation information performed at a computer device. The method includes: acquiring a target video; acquiring, according to a scene change status of the target video, a target video frame being used for location detection; performing image recognition on the target video frame to obtain masking information of the target video frame including a first region of an object of a target type in the target video frame; and determining an implantation location of recommendation information in the target video frame based on the first region. Image recognition processing is performed on the target video frame to obtain the masking information of the target video frame, so as to determine the implantation location in the target video frame on the basis of the first region corresponding to the object of the target type in the target video frame.

Abstract: A resource display method includes: obtaining one or more target sub-videos of a target video; obtaining at least one key frame of any target sub-video based on image frames of the any target sub-video; dividing any key frame of the any target sub-video into a plurality of regions according to color clustering, and using a region that meets an area requirement in the plurality of regions as a candidate region of the any key frame; using candidate regions of key frames of the any target sub-video as candidate regions of the any target sub-video; and selecting a target region from candidate regions of the target sub-videos, and displaying a resource in the target region.

Abstract: A method and a system for processing network media information are provided. The method includes: collecting historical distribution effect data of network media information; performing attribute improvement processing on the historical distribution effect data by using population attribute data and network media information management data to obtain characteristic attribute data; constructing an effect parameter estimation model corresponding to each attribute of the characteristic attribute data, and training the effect parameter estimation model; estimating an effect parameter value of each audience for target network media information according to the effect parameter estimation model; and selecting an audience whose estimated effect parameter value is greater than or equal to a specified threshold value to form an audience population package to be extracted.

Abstract: Embodiments of the present invention disclose a push information pre-selecting method and apparatus. The method includes: based on historical push data of push information including a plurality of push information items, determining a feature for calculating a predicted value, and a weight corresponding to the feature; calculating a standard deviation of the feature; determining a fluctuation probability of the standard deviation; calculating the predicted value based on the weight, the standard deviation, and the fluctuation probability, the standard deviation and the fluctuation probability being used for calculating a fluctuation value for correcting the weight; based on the predicted value, selecting push information items satisfying a preset condition; and pushing the selected push information items to a target user.

Abstract: The present disclosure discloses a method, a device, and a system for displaying media data, which belong to the field of information processing technologies. The method includes: determining at least one piece of media data corresponding to a data display position; acquiring predicted click information and predicted display information corresponding to each piece of media data; and selecting one piece of media data from all the media data according to the predicted click information and the predicted display information corresponding to each piece of media data and displaying the selected media data on the data display position.

Abstract: A method and a system for processing network media information are provided. The method includes: collecting historical distribution effect data of network media information; performing attribute improvement processing on the historical distribution effect data by using population attribute data and network media information management data to obtain characteristic attribute data; constructing an effect parameter estimation model corresponding to each attribute of the characteristic attribute data, and training the effect parameter estimation model; estimating an effect parameter value of each audience for target network media information according to the effect parameter estimation model; and selecting an audience whose estimated effect parameter value is greater than or equal to a specified threshold value to form an audience population package to be extracted.