Cox Tries Combined OTT & Pay TV Search

The ideal multiscreen interface should deliver personalized free and pay streaming video content, along with local programming, Cox Communications says in a patent published Tuesday.

Cox customers on its next-generation platform would each have their own “custom virtual channel on his/her viewing device,” Cox states in the patent, titled, “Virtual Video Channels.”

GravinoCox Senior director Video Product Development Douglas Gravino is named as lead inventor on the patent.

Abstract: Embodiments of the present invention are directed to utilizing video content available to a user from disparate sources (e.g., local video, paid streaming video, free steaming video, etc.), cross-matching the available content with known, detailed metadata, and providing

Patent

Claims:

  1. A method for populating one or more virtual channels with accessible video content, the method comprising: generating an index of user accessible video content, the user accessible content comprising broadcast content; acquiring video content; filtering the video content into a subset of video content to categorize, the filtering comprising applying a tunable algorithm to the video content, the tunable algorithm comprising parameters including at least one of popularity, geographical region, and age of content; adding descriptive tags to metadata associated with each piece of video content of the subset of video content; cross-matching the index of user accessible video content with the tagged subset of video content; analyzing the metadata associated with the cross-matched video content and mapping the cross-matched video content and associated metadata to one or more classifications; generating one or more virtual channels according to one or more classifications; populating the one or more generated virtual channels with cross-matched video content and associated metadata having a similar mapping to the one or more classifications, the cross-matched video content comprising one or more of broadcast content and local content; determining if a paid streaming content limit has been reached; and filtering the generated virtual channel to remove paid streaming content if the limit has been reached.
  1. The method of claim 1, wherein generating an index of user accessible video content includes acquiring one or more indexes of video content available to the user, the video content available to the user including one or more of free streaming video content, on-demand video content, subscription programming video content, paid streaming video content, and local video content.
  1. The method of claim 1, wherein filtering further comprises culling unwanted video content.
  1. The method of claim 1, further comprising receiving a selection of video content provided in a virtual channel and providing the selected video content to the user.
  1. The method of claim 4, wherein if the selected video content is paid streaming content and has not been previously purchased by the user, providing an interface for allowing the user to purchase the selected video content.
  1. The method of claim 1, wherein filtering video content into a subset of video content to categorize includes utilizing a filtering algorithm to filter the video content into a subset of video content to categorize according to one or more of popular video content and video content applicable to a given geographic region.
  1. The method of claim 1, wherein adding descriptive tags to metadata associated with each piece of video content of the subset of video content includes one or more or a combination of manual categorization, crowd-source categorization, and automated categorization.
  1. The method of claim 1, further comprising gathering user preference data to generate a user profile for a user.
  1. The method of claim 8, wherein gathering user preference data includes gathering preference data input by the user and gathering preference data associated with video content selection choices made by the user.
  1. The method of claim 8, further comprising: analyzing the metadata associated with the cross-matched video content and mapping the cross-matched video content and associated metadata to one or more classifications associated with the user profile; generating one or more virtual channels according to one or more classifications associated with the user profile; and populating the one or more generated virtual channels with cross-matched video content and associated metadata having a similar mapping to the one or more classifications associated with the user profile.
  1. The method of claim 1, further comprising analyzing the metadata associated with the cross-matched video content and identifying video content that is part of a series grouping.
  1. The method of claim 11, further comprising if one or more generated virtual channels comprise video content that is part of a series grouping, populating the one or more generated virtual channels with other identified video content that is part of the series grouping.
  1. The method of claim 1, further comprising: receiving authorization from a user for automated video content purchases; receiving automated video content purchasing rules from the user; analyzing the cross-matched video content and associated metadata for available paid streaming video content having a similar mapping to one or more classifications associated with the user profile, the available paid streaming video content having not been purchased previously by the user; determining a best match for a paid streaming video content purchase according to user preference data and received automated video content purchasing rules; recommending the best match for a paid streaming video content purchase to the user; receiving an indication of a selection of the recommended paid streaming video content; automatically purchasing the paid streaming video content; and providing the selected paid streaming video content to the user.
  1. A system for populating one or more virtual channels with accessible video content, the system comprising: a filtering system operable to filter video content into a subset of video content to categorize according to popularity and geographic region, the video content comprising broadcast content; a categorization engine operable to: add descriptive tags to metadata associated with each piece of video content of the subset of video content; and generate a database comprising the tagged subset of video content; a cross-match filter operable to cross-match an index of user accessible video content with the tagged subset of video content; and one or more filters operable to: analyze the metadata associated with the cross-matched video content and map the cross-matched video content and associated metadata to one or more classifications; generate one or more virtual channels according to one or more classifications; populate the one or more generated virtual channels with cross-matched video content and associated metadata having a similar mapping to the one or more classifications; determine if a paid streaming content limit has been reached; and filter the generated virtual channel to remove paid streaming content if the limit has been reached.
  1. The system of claim 14, further comprising a recommendation and purchase engine operable to: receive authorization from a user for automated video content purchases; receive automated video content purchasing rules from the user; analyze the cross-matched video content and associated metadata for available paid streaming video content having a similar mapping to one or more classifications associated with the user profile, the available paid streaming video content having not been purchased previously by the user; determine a best match for a paid streaming video content purchase according to user preference data and received automated video content purchasing rules; recommend the best match for a paid streaming video content purchase to the user; receive an indication of a selection of the recommended paid streaming video content; automatically purchase the paid streaming video content; and provide the selected paid streaming video content to the user.
  1. The system of claim 14, the one or more filters further operable to: gather user preference data to generate a user profile for a user, wherein gathering user preference data includes gathering preference data input by the user and gathering preference data associated with video content selection choices made by the user; analyze the metadata associated with the cross-matched video content and map the cross-matched video content and associated metadata to one or more classifications associated with the user profile; generate one or more virtual channels according to one or more classifications associated with the user profile; and populate the one or more generated virtual channels with cross-matched video content and associated metadata having a similar mapping to the one or more classifications associated with the user profile.
  1. The system of claim 16, the one or more filters being further operable to analyze the metadata associated with the cross-matched video content and identify video content that is part of a series grouping.
  1. The system of claim 17, further comprising if one or more generated virtual channels comprising video content that is part of a series grouping, the one or more second filters being further operable to populate the one or more generated virtual channels with other identified video content that is part of the series grouping.
  1. A non-transitory computer-readable medium containing computer-executable instructions which when executed by a computer perform a method for populating one or more virtual channels with accessible video content, the method comprising: generating an index of user accessible video content, the user accessible content including one or more of free streaming video content, on-demand video content, subscription programming video content, paid streaming video content, and local video content; gathering user preference data to generate a user profile for the user, wherein gathering user preference data includes gathering preference data input by the user and gathering preference data associated with video content selection choices made by the user; acquiring video content; filtering the video content into a subset of video content to categorize, the subset of video content being associated with popular video content and a geographic region; adding descriptive tags to metadata associated with each piece of video content of the subset of video content, the tagging including one or more or a combination of manual categorization, crowd-source categorization, and automated categorization; generating a database comprising the tagged subset of video content; cross-matching the index of user accessible video content with the categorized subset of video content; analyzing the metadata associated with the cross-matched video content and mapping the cross-matched video content and associated metadata to one or more classifications, one or more of the one or more classifications being associated with the user profile; identifying video content that is part of a series grouping; generating one or more virtual channels according to one or more classifications; populating the one or more generated virtual channels with cross-matched video content and associated metadata having a similar mapping to the one or more classifications, and if one or more generated virtual channels comprise video content that is part of a series grouping, populating the one or more generated virtual channels with other identified video content that is part of the series grouping, the cross-matched video content comprising broadcast content and local content; determining if a paid streaming content limit has been reached; and filtering the generated virtual channel to remove paid streaming content if the limit has been reached.
  1. The computer-readable medium of claim 19, the method further comprising: receiving authorization from a user for automated video content purchases; receiving automated video content purchasing rules from the user; analyzing the cross-matched video content and associated metadata for available paid streaming video content having a similar mapping to one or more classifications associated with the user profile, the available paid streaming video content having not been purchased previously by the user; determining a best match for a paid streaming video content purchase according to user preference data and received automated video content purchasing rules; recommending the best match for a paid streaming video content purchase to the user; receiving an indication of a selection of the recommended paid streaming video content; automatically purchasing the paid streaming video content; and providing the selected paid streaming video content to the user.