Abstract: A method, computer-readable medium, and apparatus for modeling data of a plurality of services for providing a new service are disclosed. For example, a method may include a processor for generating a first policy from a first service by a first policy model using machine learning for processing first data of the first service, generating a second policy from a second service by a second policy model using machine learning for processing second data of the second service, wherein the first service and the second service are different, and implementing one or more functions for a new service using the first policy and the second policy.

Abstract: A method, computer-readable medium, and apparatus for configuring a software defined network via machine learning are disclosed. For example, a method may generate a first policy for a first service by a first policy model using machine learning for processing first data of the first service, the first service being implement by at least one first virtual component of a software defined network, determine whether the first policy is to be applied to a second service, the second service being implement by at least one second virtual component of the software defined network, apply the first policy to the second service when the first policy is deemed to be applicable to the second service, generate a second policy for the second service, and implement the second policy in the second service, wherein the first service and the second service are provided by a single service provider.

Abstract: A method, computer-readable medium, and apparatus for modeling data of a service for providing a policy are disclosed. For example, a method may include a processor for generating a first policy for a first service by a first policy model using machine learning for processing first data of the first service, determining whether the first policy is to be applied to a second service, applying the first policy to the second service when the first policy is deemed to be applicable to the second service, wherein the applying the first policy provides the first policy to a second policy model using machine learning for processing second data of the second service, generating a second policy for the second service, and implementing the second policy in the second service, wherein the first service and the second service are provided by a single service provider.

Abstract: Aspects of the subject disclosure may include, for example, facilitating access to a synopsis of a missed portion of a media program, identifying subject matter in a segment of content in the media program that has not been presented, determining a particular time for presenting the summary according to the subject matter in the segment of content, and initiating a presentation of the summary at the particular time. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, receiving a plurality of media content instances, where each media content instance of the plurality of media content instances comprises origination information, identifying a common event from the origination information of each media content instance of the plurality of media content instances, determining a plurality of viewing perspectives of the plurality of media content instances responsive to identifying the common event, and sending an alert to a social network to enable access to a viewing perspective of the plurality of viewing perspectives.

Abstract: A system that incorporates the subject disclosure may perform operations, for example, including determining a first correlation value between a behavior of a first audience member and a subject matter being presented at a display processor, wherein the subject matter being presented at the display is observable by the first audience member. A second correlation value is determined between the behavior of the first audience member and a characteristic of an environment in a vicinity of the display and the first audience member. Responsive to the second correlation value exceeding the first correlation value, a determination is made as to whether a present channel selection resulting from user input initiated by the first audience member is responsive to the characteristic of the environment influencing the audience member more than the subject matter being presented at the display. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, analyzing content flow data in a communication network to obtain flow statistics; the statistics are aggregated to construct a model of the content flow based on the aggregated flow statistics. Operations of network nodes are predicted based on the model; a content delivery path in the communication network is identified. A quality of service is detected for network nodes on the content delivery path. The detected quality of service is compared with a predicted quality of service based on the model; a network anomaly is detected based on the comparing. The content flow on the content delivery path is adjusted responsive to detection of the network anomaly. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, generating narrative descriptions corresponding to visual features, visual events, and interactions there between for media content, where the narrative descriptions are associated with time stamps of the media content, and presenting the media content and an audio reproduction of the narrative descriptions, wherein the audio reproduction is synchronized to video of the media content according to the time stamps. Other embodiments are disclosed.

Abstract: A method includes receiving, at a processor, a first data stream from a first platform and a second data stream from a second platform. The first data stream includes content and the second data stream includes the content. The method also includes performing an analysis operation on the first data stream and the second data stream to interpret the content. Performing the analysis operation includes performing a statistical analysis on the first data stream and the second data stream using one or more Artificial Neural Network (ANN) nodes of an analytical network. Performing the analysis operation also includes performing a syntactic analysis on the first data stream and the second data stream using one or more Markov Logic Network (MLN) nodes of the analytical network.

Abstract: A method and apparatus for providing a recommended action are disclosed. For example, the method receives first data that is measured via at least one sensor deployed at a venue, receives second data from at least one user endpoint device present at the venue, wherein the second data comprises data that is measured via a sensor associated with the at least one user endpoint device, applies a perception model of the venue to the first data and the second data that are received, generates at least one recommended action when a threshold is reached, wherein the threshold is established for generating the at least one recommended action, and provides an update to the perception model of the venue based on the at least one recommended action that is generated.

Abstract: A method includes analyzing media data to determine characteristics of a media content item corresponding to the media data based on first visual information of the media content item. The method includes analyzing the characteristics of the media content item based on a media popularity data structure to generate a prediction of whether the media content item is likely to exceed a popularity threshold within a particular period of time. The method further includes generating a suggested content change to the media content item in response to the prediction indicating that the media content item is not likely to exceed the popularity threshold within the particular period of time.

Abstract: Aspects of the subject disclosure may include, for example, generating a summary of a missed portion of a media program, identifying subject matter in a segment of content in the media program that has not been presented, determining a particular time for presenting the summary according to the subject matter in the segment of content, and initiating a presentation of the summary at the particular time. Other embodiments are disclosed.

Abstract: Devices, computer-readable media, and methods are disclosed for assigning a service to a vehicle-based mobile node. For example, a processor deployed in a communication network may receive a request for the service from a mobile endpoint device, determine a route of the mobile endpoint device, determine a route of the vehicle-based mobile node, and assign the service to the vehicle-based mobile node when the route of the mobile endpoint device and the route of the vehicle-based mobile node coincide.

Abstract: A method includes accessing information identifying user devices, and accessing media consumption data indicating content requests corresponding to the user devices. The method also includes determining expected locations of the user devices based on the information, and determining forecasted content requests based on the media consumption data. The method further includes generating a pre-caching schedule based on the forecasted content requests and the expected locations, and determining that the pre-caching schedule indicates that particular media data is to be provided via a multicast transmission to a first user device and to a second user device. The method also includes sending an instruction to the first user device directing the first user device to store the particular media data. The method includes sending, responsive to a request from the second user device, the particular media data via the multicast transmission to the first user device and to the second user device.

Abstract: Aspects of the subject disclosure may include, for example, generating narrative descriptions corresponding to visual features, visual events, and interactions there between for media content, where the narrative descriptions are associated with time stamps of the media content, and presenting the media content and an audio reproduction of the narrative descriptions, wherein the audio reproduction is synchronized to video of the media content according to the time stamps. Other embodiments are disclosed.

Abstract: A method includes determining a level of user engagement associated with content of a program displayed at a first display device and comparing the level of user engagement to a threshold. If the level of user engagement satisfies the threshold, the method includes generating an advertisement associated with the content displayed at the first display device and determining whether the user is within a distance of the first display device during a commercial break of the program. The method also includes displaying the advertisement at the first display device during the commercial break if the user is within the distance of the first display device and displaying the advertisement at a second display device during the commercial break if the user is not within the distance of the first display device. If the level of user engagement fails to satisfy the threshold, generation of the advertisement is bypassed.

Abstract: A method includes receiving media data corresponding to a media content item. The method further includes analyzing the media data to determine characteristics of the media content item based on first visual information contained in the media content item. The method further includes analyzing the characteristics of the media content item based on a media popularity model to generate a prediction of whether the media content item is likely to exceed a popularity threshold within a particular period of time. The method further includes determining, at the computing device, a network location at which to store the media content item based on the prediction.

Abstract: Aspects of the subject disclosure may include, for example, gathering activity information for a user of a media processor determining time stamps for the activity information, generating a model of future user activity based on the time stamps by extrapolating when future events will be performed by the user, determining recommended media content for the future events, requesting the media files at the recommendation time point for the one of the plurality of media files, storing the media files, and presenting a recommendation to present the media files at the recommendation time point. Other embodiments are disclosed.

Abstract: A method includes receiving, at a processor, a first data stream from a first platform and a second data stream from a second platform. The first data stream includes content and the second data stream includes the content. The method also includes performing an analysis operation on the first data stream and the second data stream to interpret the content. Performing the analysis operation includes performing a statistical analysis on the first data stream and the second data stream using one or more Artificial Neural Network (ANN) nodes of an analytical network. Performing the analysis operation also includes performing a syntactic analysis on the first data stream and the second data stream using one or more Markov Logic Network (MLN) nodes of the analytical network.

Abstract: A method includes receiving, at a network device, a request from a device for a summary of media content. The method includes accessing the media content in response to the request and performing an analysis of the media content based on a user profile associated with the device. The user profile indicates preferences, and the analysis determines whether the media content includes a feature indicated by a preference of the preferences. In response to the analysis indicating that the media content includes the feature, the method includes selecting representative frames of the media content based on the analysis and sending the representative frames to the device.