Abstract: Images and/or videos may be recommended to a developer based on a classifier. The classifier may determine an application metric that may measure the likelihood that an application is successful for applications on an application store. The system may extract and/or determine features from images and/or videos associated with a training set of applications that are deemed successful. A classifier may be trained on the training set of applications to determine which features of the images and/or videos are associated with the application metric. The classifier may be applied to new and/or existing applications on the application store to generate a recommendation of which images the developer of the application should use to increase the likelihood that the application will be successful.

Abstract: A system and method of recommending a bundle of content items to a user, including storing a plurality of content items in a computer system, determining a respective co-selection score for each pair of content items among the plurality of content items, the co-selection score indicating a probability that a given pair of content items among the plurality of content items will both be downloaded by a user of the computer system, and outputting, to a first user, a plurality of content items comprising a sub-set of the plurality of content items.

Abstract: Disclosed herein are methods and apparatuses for compressing a video signal. In one embodiment, the method includes storing a function derived from a set of human ratings in a memory, identifying within at least a portion of the video signal at least one content-based feature, inputting the at least one identified content-based feature into the stored function, determining a compression ratio based on the function using a processor and generating a compressed video signal at the determined compression ratio.

Abstract: A system and method for associating videos with geographic locations is disclosed. The system comprises a communication module, a location module, a tagging module and a database association module. The communication module receives a video uploaded by a content provider and a set of video data describing the video. The location module determines that the video describes a geographic location included in a geographic map based at least in part on the video data. The tagging module determines one or more travelling tags for the video based at least in part on the video data. The database association module associates the video and the one or more travelling tags with the geographic location so that the video with the one or more travelling tags is included in the geographic map.

Abstract: A system and method for associating videos with geographic locations is disclosed. The system comprises a communication module, a location module, a tagging module and a database association module. The communication module receives a video uploaded by a content provider and a set of video data describing the video. The location module determines that the video describes a geographic location included in a geographic map based at least in part on the video data. The tagging module determines one or more travelling tags for the video based at least in part on the video data. The database association module associates the video and the one or more travelling tags with the geographic location so that the video with the one or more travelling tags is included in the geographic map.

Abstract: A system and method provide a soundtrack recommendation service for recommending one or more soundtrack for a video (i.e., a probe video). A feature extractor of the recommendation service extracts a set of content features of the probe video and generates a set of semantic features represented by a signature vector of the probe video. A video search module of the recommendation service is configured to search for a number of video candidates, each of which is semantically similar to the probe video and has an associated soundtrack. A video outlier identification module of the recommendation service identifies video candidates having an atypical use of their soundtracks and ranks the video candidates based on the typicality of their soundtrack usage. A soundtrack recommendation module selects the soundtracks of the top ranked video candidates as the soundtrack recommendations to the probe video.

Abstract: A mechanism for automatic quantification of multimedia production quality is presented. A method of embodiments includes assembling data samples from users, the data samples indicating a relative production quality of a set of content items based on a comparison of production quality between content items in the set, extracting content features from each of the content items in the set, and learning, based on the data samples from the plurality of users, a statistical model on the extracted content features, wherein the learned statistical model can predict a production quality of another content item that is not part of the set of content items.

Abstract: A classifier training system trains classifiers for inferring the geographic locations of videos. A number of classifiers are provided, where each classifier corresponds to a particular location and is trained from a training set of videos that have been labeled as representing the location. In one embodiment, the training set is further restricted to those videos in which a landmark matching the location label is detected. The classifier training system extracts, from each of these videos, features that characterize the video, such as audiovisual features, text features, address features, landmark features, and category features. Based on these features, the classifier training system trains a location classifier for the corresponding location. Each of the location classifiers can be applied to videos without associated location labels to predict whether, or how strongly, the video represents the corresponding location.

Abstract: A demographics analysis trains classifier models for predicting demographic attribute values of videos and users not already having known demographics. In one embodiment, the demographics analysis system trains classifier models for predicting demographics of videos using video features such as demographics of video uploaders, textual metadata, and/or audiovisual content of videos. In one embodiment, the demographics analysis system trains classifier models for predicting demographics of users (e.g., anonymous users) using user features based on prior video viewing periods of users. For example, viewing-period based user features can include individual viewing period statistics such as total videos viewed. Further, the viewing-period based features can include distributions of values over the viewing period, such as distributions in demographic attribute values of video uploaders, and/or distributions of viewings over hours of the day, days of the week, and the like.

Abstract: A system, apparatus, and method for video categorization using heterogeneous signals are disclosed. One aspect of the disclosed embodiments is a method for categorizing a plurality of video streams. The method includes determining a plurality of features of at least some of the plurality of video streams, determining a category of a first video stream of the plurality of video stream based on its plurality of features, identifying, using a processor, a relationship between the first video stream and a second video stream of the plurality of videos, the relationship having an associated weight, and updating, using the processor, the category of the first video stream based on a first message determined using the associated weight.

Abstract: Disclosed are methods for automatically generating commands to transform a video sequence based on information regarding speaking participants derived from the audio and video signals. The audio stream is analyzed to detect individual speakers and the video is optionally analyzed to detect lip movement to determine a probability that a detected participant is speaking. Commands are then generated to transform the video stream consistent with the identified speaker.

Abstract: Methods and apparatus for suggesting image, video, and image album titles are presented. A machine-learning service executing on a mobile platform receives feature-related data. The feature-related data includes image-related data related to one or more images received from an application executing on the mobile platform and platform-related data received from the mobile platform. The image-related data and the platform-related data differ. The machine-learning service generates a title related to the one or more images by performing a machine-learning operation on the feature-related data. The machine-learning service sends the title related to the one or more images to the application.

Abstract: A classifier training system learns classifiers for categories by combining data from a category-instance repository comprising relationships between categories and more specific instances of those categories with a set of video classifiers for different concepts. The category-instance repository is derived from the domain of textual documents, such as web pages, and the concept classifiers are derived from the domain of video. Taken together, the category-instance repository and the concept classifiers provide sufficient data for obtaining accurate classifiers for categories that encompass other lower-level concepts, where the categories and their classifiers may not be obtainable solely from the video domain.

Abstract: Certain embodiments of the disclosed technology include systems and methods for determining the priority of a notification on a mobile device using machine learning. Other aspects of the disclosed technology include selectively displaying notifications based on the priority of a notification.

Abstract: A system and method provide a soundtrack recommendation service for recommending one or more soundtrack for a video (i.e., a probe video). A feature extractor of the recommendation service extracts a set of content features of the probe video and generates a set of semantic features represented by a signature vector of the probe video. A video search module of the recommendation service is configured to search for a number of video candidates, each of which is semantically similar to the probe video and has an associated soundtrack. A video outlier identification module of the recommendation service identifies video candidates having an atypical use of their soundtracks and ranks the video candidates based on the typicality of their soundtrack usage. A soundtrack recommendation module selects the soundtracks of the top ranked video candidates as the soundtrack recommendations to the probe video.

Abstract: Disclosed herein are methods and apparatuses for compressing a video signal. In one embodiment, the method includes storing a function derived from a set of human ratings in a memory, identifying within at least a portion of the video signal at least one content-based feature, inputting the at least one identified content-based feature into the stored function, determining a compression ratio based on the function using a processor and generating a compressed video signal at the determined compression ratio.

Abstract: A system and method provide a soundtrack recommendation service for recommending one or more soundtrack for a video (i.e., a probe video). A feature extractor of the recommendation service extracts a set of content features of the probe video and generates a set of semantic features represented by a signature vector of the probe video. A video search module of the recommendation service is configured to search for a number of video candidates, each of which is semantically similar to the probe video and has an associated soundtrack. A video outlier identification module of the recommendation service identifies video candidates having an atypical use of their soundtracks and ranks the video candidates based on the typicality of their soundtrack usage. A soundtrack recommendation module selects the soundtracks of the top ranked video candidates as the soundtrack recommendations to the probe video.

Abstract: Certain embodiments of the disclosed technology include systems and methods for determining the priority of a notification on a mobile device using machine learning. Other aspects of the disclosed technology include selectively displaying notifications based on the priority of a notification.

Abstract: In one example, a method includes determining, by a computing device, a plurality of features. Each feature from the plurality of features may be usable to determine a dominant hand of a user of the computing device. The method also includes receiving, by the computing device, a plurality of input values, each input value from the plurality of input values corresponding to the respective plurality of features, and determining, using a probabilistic model and based at least in part on at least one input value from the plurality of input values corresponding to the respective feature from the plurality of features, a hand of the user as a dominant hand of the user. The method also includes generating, based at least in part on the determined dominant hand of the user, a graphical user interface for display at a presence-sensitive display operatively coupled to the computing device.

Abstract: In one example, a method includes determining, by a computing device, a plurality of features. Each feature from the plurality of features may be usable to determine a dominant hand of a user of the computing device. The method also includes receiving, by the computing device, a plurality of input values, each input value from the plurality of input values corresponding to the respective plurality of features, and determining, using a probabilistic model and based at least in part on at least one input value from the plurality of input values corresponding to the respective feature from the plurality of features, a hand of the user as a dominant hand of the user. The method also includes generating, based at least in part on the determined dominant hand of the user, a graphical user interface for display at a presence-sensitive display operatively coupled to the computing device.