Abstract: Disclosed are systems and methods for improving interactions with and between computers in content searching, generating, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods automatically determine media content to communicate to a user based on the user's location. The disclosed systems and methods enable novel media content distribution to a user based on 1) the location of the user (i.e., physical location or geo-location), 2) other users' classified relationships to the location; and 3) user generated media content by the classified other users.

Abstract: Disclosed herein are aspects associated with contextual, or related, media enrichment presentation item of a media object served via the internet. A request to annotate a media object in connection with the media object's presentation is received, and a media object identifier and a profile identifier are obtained. The media object's information is retrieved using the media object identifier, and a profile is retrieved using the profile identifier. A response including one or more references to one or more media enrichment presentation items is transmitted, each reference to a media enrichment presentation item comprising information for use in retrieving the media enrichment presentation item for presentation in connection with presentation of the media object.

Abstract: The present disclosure is descriptive of discovering structure, content, and context of a media event, e.g., a live media event, using real-time discussions that unfold through short messaging services. Generally, a sampling of short messages of a plurality of users is obtained. The sampling of short messages corresponds to a media event. A segment in the media event is identified using the sampling of short messages, and at least one term taken from the sampling of short messages is identified. The at least one term is indicative of a context of the identified segment.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content providing, generating, securing and/or hosting systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the security and quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide added security features and functionality to media files through computerized, automated encoding and decoding of portions of media file content such that identified portions of the content are obfuscated upon display and communication to other users. The disclosed systems and methods provide a novel, computerized security feature(s) that protects data of media files from unintended exposure to third parties.

Abstract: Disclosed herein are aspects associated with contextual, or related, media enrichment presentation item of a media object served via the internet. A request to annotate a media object in connection with the media object's presentation is received, and a media object identifier and a profile identifier are obtained. The media object's information is retrieved using the media object identifier, and a profile is retrieved using the profile identifier. A response including one or more references to one or more media enrichment presentation items is transmitted, each reference to a media enrichment presentation item comprising information for use in retrieving the media enrichment presentation item for presentation in connection with presentation of the media object.

Abstract: Disclosure includes system, method and architecture for selecting supplemental digital content using visual appearance. Digital content that is visually similar, or dissimilar, to digital content requested by a user can he identified and provided for presentation with the requested content. The additional digital content is visually congruent, or visually incongruent, with content requested by a user, such that the additional content is similar, or dissimilar, to the requested content from a visual standpoint. In a presentation of the requested content, the presentation position of each additional content item relative to the presentation position of each requested content can be identified using visual congruence, or visual incongruence.

Abstract: The present disclosure is descriptive of discovering structure, content, and context of a media event, e.g., a live media event, using real-time discussions that unfold through short messaging services. Generally, a sampling of short messages of a plurality of users is obtained. The sampling of short messages corresponds to a media event. A segment in the media event is identified using the sampling of short messages, and at least one term taken from the sampling of short messages is identified. The at least one term is indicative of a context of the identified segment.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content searching, generating, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods automatically determine media content to communicate to a user based on the user's location. The disclosed systems and methods enable novel media content distribution to a user based on 1) the location of the user (i.e., physical location or geo-location), 2) other users' classified relationships to the location; and 3) user generated media content by the classified other users.

Abstract: A digital document is represented as a set of codes comprising indices into a feature space comprising a number of subspaces, each code corresponds to one subspace and identifying a cell within the subspace. Each digital document can be represented by a code set, and the code set can be used as selection criteria for identifying a number of digital documents using each digital document's corresponding code set. By way of some non-limiting examples, digital document code sets can be used to identify similar or different digital images, used to identify duplicate or nearly-duplicate digital images, used to identify similar and/or different digital images for inclusion in a recommendation, used to identify and rank digital images in a set of search results.

Abstract: A digital document is represented as a set of codes comprising indices into a feature space comprising a number of subspaces, each code corresponds to one subspace and identifying a cell within the subspace. Each digital document can be represented by a code set, and the code set can be used as selection criteria for identifying a number of digital documents using each digital document's corresponding code set. By way of some non-limiting examples, digital document code sets can be used to identify similar or different digital images, used to identify duplicate or nearly-duplicate digital images, used to identify similar and/or different digital images for inclusion in a recommendation, used to identify and rank digital images in a set of search results.

Abstract: Techniques are provided for efficiently identifying relevant product images based on product items detected in a query image. In general, a query image may represent a digital image in any format that depicts a human body and one or more product items. For example, a query image may be an image for display on a webpage, an image captured by a user using a camera device, or an image that is part of a media content item, such as a frame from a video. Product items may be detected in a query image by segmenting the query image into a plurality of image segments and clustering one or more of the plurality image segments into one or more image segment clusters. The resulting image segments and image segment clusters may be used to search for visually similar product images.

Abstract: Disclosed herein are aspects associated with contextual, or related, media enrichment presentation item of a media object served via the internet. A request to annotate a media object in connection with the media object's presentation is received, and a media object identifier and a profile identifier are obtained. The media object's information is retrieved using the media object identifier, and a profile is retrieved using the profile identifier. A response including one or more references to one or more media enrichment presentation items is transmitted, each reference to a media enrichment presentation item comprising information for use in retrieving the media enrichment presentation item for presentation in connection with presentation of the media object.

Abstract: Disclosed herein are aspects associated with contextual, or related, media enrichment presentation item of a media object served via the internet. A request to annotate a media object in connection with the media object's presentation is received, and a media object identifier and a profile identifier are obtained. The media object's information is retrieved using the media object identifier, and a profile is retrieved using the profile identifier. A response including one or more references to one or more media enrichment presentation items is transmitted, each reference to a media enrichment presentation item comprising information for use in retrieving the media enrichment presentation item for presentation in connection with presentation of the media object.

Abstract: The present disclosure is descriptive of discovering structure, content, and context of a media event, e.g., a live media event, using real-time discussions that unfold through short messaging services. Generally, a sampling of short messages of a plurality of users is obtained. The sampling of short messages corresponds to a media event. A segment in the media event is identified using the sampling of short messages, and at least one term taken from the sampling of short messages is identified. The at least one term is indicative of a context of the identified segment.

Abstract: Software for supervised learning extracts a set of pixel-level features from each source image in collection of source images. Each of the source images is associated with a thumbnail created by an editor. The software also generates a collection of unique bounding boxes for each source image. And the software calculates a set of region-level features for each bounding box. Each region-level feature results from the aggregation of pixel values for one of the pixel-level features. The software learns a regression model, using the calculated region-level features and the thumbnail associated with the source image. Then the software chooses a thumbnail from a collection of unique bounding boxes in a new image, based on application of the regression model. The software uses a thumbnail received from an editor instead of the chosen thumbnail, if the chosen thumbnail is of insufficient quality as measured against a scoring threshold.

Abstract: This patent discloses a system to compile a landmark image search result. The system may determine a rank of each image within a visual cluster according to at least one of a low-level self-similarity score, a low-level discriminative modeling score, and a point wise linking score. The landmark image search result may be compiled as a function of the rank of each image.

Abstract: The present disclosure is descriptive of discovering structure, content, and context of a media event, e.g., a live media event, using real-time discussions that unfold through short messaging services. Generally, a sampling of short messages of a plurality of users is obtained. The sampling of short messages corresponds to a media event. A segment in the media event is identified using the sampling of short messages, and at least one term taken from the sampling of short messages is identified. The at least one term is indicative of a context of the identified segment.

Abstract: Some embodiments of the invention provide techniques for an advertisement mask and a target media content being jointly encoded, transformed, and progressively rendered for presentation to a user. Specifically, a request for the target media content by a user is received. The target media content and the advertisement mask are scaled and divided into equally sized blocks and, further, jointly encoded into a compressed media file. Transformation of the content of the compressed media file is followed by progressively loading and rendering the advertisement mask and a partially obscured view of the media content. As the target media content is transmitted and fully rendered, the advertisement mask gradually decreases in opacity until it is removed for presentation of the fully-rendered target media content.

Abstract: The present disclosure is descriptive of discovering structure, content, and context of a media event, e.g., a live media event, using real-time discussions that unfold through short messaging services. Generally, a sampling of short messages of a plurality of users is obtained. The sampling of short messages corresponds to a media event. A segment in the media event is identified using the sampling of short messages, and at least one term taken from the sampling of short messages is identified. The at least one term is indicative of a context of the identified segment.

Abstract: Software for supervised learning extracts a set of pixel-level features from each source image in collection of source images. Each of the source images is associated with a thumbnail created by an editor. The software also generates a collection of unique bounding boxes for each source image. And the software calculates a set of region-level features for each bounding box. Each region-level feature results from the aggregation of pixel values for one of the pixel-level features. The software learns a regression model, using the calculated region-level features and the thumbnail associated with the source image. Then the software chooses a thumbnail from a collection of unique bounding boxes in a new image, based on application of the regression model. The software uses a thumbnail received from an editor instead of the chosen thumbnail, if the chosen thumbnail is of insufficient quality as measured against a scoring threshold.