Methods and systems for detecting and predicting anomalies include processing frames of a video stream to determine values of a feature corresponding to each frame. A feature time series is generated that corresponds to values of the identified feature over time. A matrix profile is generated that identifies similarities of sub-sequences of the time series to other sub-sequences of the feature time series. An anomaly is detected by determining that a value of the matrix profile exceeds a threshold value. An automatic action is performed responsive to the detected anomaly.

A computerized method, system for, and computer-readable medium operable to: retrieve program details data about at least one media program. Retrieve social media posts involving the at least one media program. Match the retrieved program details data with the retrieved social media posts to find matching locations. Store time offset data corresponding to the matched locations within the at least one media program into at least one micropost. Rank the at least one media program by the number of microposts corresponding to the at least one media program. Present the at least one media program, each of the at least one media program with at least one micropost, wherein the at least one micropost comprises a link to the original social media page hosting the social media post and a video deeplink that plays a time off-set video, the time off-set video starting from the stored time offset data.

A video recommending method, including: obtaining videos, the video including long videos and short videos; obtaining a subset of the long videos, of which video attribute values are greater than corresponding attribute thresholds; obtaining a watching record of a user, and obtaining similarities between the short videos and videos in the watching record, to extract a preset quantity of short videos having highest similarities; and recommending the subset of the long videos, of which video attribute values are greater than corresponding attribute thresholds, to the user, and/or recommending the preset quantity of short videos having highest similarities to the user.

The playback of video content upon a display is enhanced through the unobtrusive presentation of extrinsic data upon the same display. A video content feature is rendered on a display. A quantity of extrinsic data relevant to a current time in the video content feature is determined based at least in part on viewing history of a user. A graphical element presenting at least a portion of the extrinsic data is rendered on the display while the video content feature is also being rendered on the display.

In general, in one aspect, a method includes compiling user interaction statistics for a set of content items displayed in association with a first target media document having a non-textual portion, at least some of the content items associated with one or more keywords, based on the interaction statistics, associating the first target media document with at least some of the keywords associated with the content items, and based on a common attribute of the first target media document and a second target media document having a non-textual portion, associating the second target media document with at least some of the keywords assigned to the first target media document. Other aspects include corresponding systems, apparatus, and computer programs stored on computer storage devices.

The present disclosure provides a system and method for recommending dynamic, adaptive and non-sequentially assembled videos. The method includes reception of a set of preference data and a set of user authentication data. The method includes development of an interest profile of the user. The method includes fetching of the one or more tagged videos. The method includes fragmentation of each tagged video into the one or more tagged fragments and segregation of one or more mapped fragments into one or more logical sets of mapped fragments. The method includes mining of semantic context information from each mapped fragment and each logical set of mapped fragments. The method includes clustering of the one or more logical sets of mapped fragments and assembling of the one or more logical clusters of mapped fragments to obtain a set of assembled videos. The method includes recommendation of the set of assembled videos.

The present disclosure provides a method and system for sharing a real time, dynamic, adaptive and non-linearly assembled video on one or more publisher platforms. The method includes collection of a first set of information associated with a publisher platform of the one or more publisher platforms and fetching a set of preference data of the user from the publisher platform in the real time. The method includes fragmentation of each tagged video into the one or more tagged fragments and segregation of one or more mapped fragments into one or more logical sets of mapped fragments. The method includes mining of semantic context information and clustering of the one or more logical sets of mapped fragments into the one or more logical clusters of mapped fragments. The method includes assembling the one or more logical clusters of mapped fragments and sharing an assembled video on the publisher platform.

The present disclosure provides a method and system for real time, dynamic, adaptive and non-sequential assembling of one or more mapped fragments of one or more tagged videos. The method includes a step of receiving a set of preference data from pre-defined selection criteria and set of user authentication data. The method includes another step of fetching the one or more tagged videos from the digitally processed repository of videos. The method includes yet another step of fragmenting each tagged video of the one or more tagged videos into the one or more tagged fragments and clustering one or more logical sets of mapped fragments into one or more logical clusters of mapped fragments. The method includes yet another step of assembling at least one of the one or more logical clusters of mapped fragments in a pre-defined order of preference to obtain an assembled video.

The present disclosure provides a system and method for enabling navigation to one or more discrete segments of a real time dynamic and adaptive non-linear, non-sequentially assembled video. The method includes reception of a set of preference data associated with a user from a pre-defined selection criteria and a set of user authentication data. Accordingly, the method includes fetching of one or more tagged videos related to the set of preference data. The method includes fragmentation of the one or more tagged videos into the one or more tagged fragments. Further, the method includes clustering of one or more mapped fragments in a pre-defined order of preference. Furthermore, the method includes insertion of one or more interactive navigation options in one or more regions. Also, the method includes serving of the assembled video and inserted one or more interactive navigation options to the user.

A system and method for navigating digital media assets including a navigation system configured to receive a search query in response to a user input and process the search query by applying the search query to a search index of digital media asset conventional and time-based metadata and determining search results of titles of and start points in time within digital media assets that satisfy the search query. The navigation system may then display the search results to the user through the user interface. The search results may be displayed in a hierarchical format, wherein the title of the digital media asset is displayed and upon selecting the title of the digital media asset, the start points in time within that digital media asset are displayed or played as a video to the user through the user interface.