- Number
- 11509962
- Published
- 2022-11-22
- Filed
- 2020-12-14
- Assignee
- Disney Enterprises, Inc.
- Inventors
- Eivy; Adam D., Navarre; Katharine S., Stapler; Ricky Kane
- CPC
- H04N21/4532; H04N21/466; H04N21/8133; H04N21/252; H04N21/25883; H04N21/25891; H04N21/8549; H04N21/4755
- Verdict
- Set aside content curation/compilation, business
- Source
- Google Patents · FreePatentsOnline
Abstract
A content compilation system includes a computing platform having a hardware processor and a memory storing a software code configured to provide an editorial interface. The hardware processor executes the software code to receive compilation authoring data via the editorial interface, identify one or more end-user(s) for receiving a content compilation, access a consumption profile of the end-user(s), obtain, using the consumption profile and a first authoring criterion in the compilation authoring data, content items from one or more content sources. The software code further aggregates, using a second authoring criterion in the compilation authoring data, the content items into content subsets, groups, using a third authoring criterion, at least some of the content subsets to produce the content compilation, computes a desirability score predicting the desirability of the content compilation to the end-user(s), and provides, when the desirability score satisfies a predetermined threshold, the content compilation to the end-user(s).
Background
BACKGROUND (1) Digital media content depicting sports, news, movies, television (TV) programming, print media, and music, for example, is consistently sought out and enjoyed by consumers. Due to its popularity with consumers, ever more digital media content is being produced and made available for distribution, so much so in fact that the availability of new, topical, content far exceeds the capacity for even the most ardent consumers to discover and evaluate. (2) One conventional approach to making new content easier for a consumer to become aware of is the use of synopses, either brief text descriptions or visual cues, such as thumbnails, for consumers to review. While useful, these synopses typically describe items of content in isolation, and fail to provide any guidance with respect to other items of related or complementary content. Moreover, as a result of the continual proliferation of new content, the individual content items that might be combined to present related subject matter in a more entertaining or informative light are too numerous and too varied to be aggregated and reviewed by a human consumer, or even a trained human editor. Due to the resources often devoted to developing new content, the efficiency and effectiveness with which collections of content likely to be desirable to consumers can be introduced to those consumers has become increasingly important to the producers, owners, and distributors of digital media content.
Claims
1. A content compilation system comprising: a computing platform having a hardware processor and a system memory; a trained machine learning model stored in the system; and a software code stored in the system memory, the software code configured to provide an editorial interface; the hardware processor configured to execute the software code to: receive compilation authoring data via the editorial interface; identify one or more end-users for receiving a content compilation; access a consumption profile of the one or more end-users; obtain, using the consumption profile and a first authoring criterion included in the compilation authoring data, a plurality of content items from at least one content source; aggregate, using a second authoring criterion included in the compilation authoring data, the plurality of content items into a plurality of content subsets; group, using a third authoring criterion included in the compilation authoring data, at least some of the plurality of content subsets; obtain a dataset of compilation authoring data generated by a human editor; generate, using the trained machine learning model and the dataset, a compilation authoring template in an automated process; produce the content compilation, using the compilation authoring template, the at least some of the plurality of content subsets, and the consumption profile of the one or more end-users; compute a desirability score predicting a desirability of the content compilation to the one or more end-users; and provide, when the desirability score satisfies a predetermined threshold, the content compilation to the one or more end-users. ||
11. A method for use by a content compilation system including a computing platform having a hardware processor and a system memory storing a trained machine learning model and a software code configured to provide an editorial interface, the method comprising: receiving, by the software code executed by the hardware processor, compilation authoring data via the editorial interface; identifying, by the software code executed by the hardware processor, one or more end-users for receiving a content compilation; accessing, by the software code executed by the hardware processor, a consumption profile of the one or more end-users; obtaining, by the software code executed by the hardware processor and using the consumption profile and a first authoring criterion included in the compilation authoring data, a plurality of content items from at least one content source; aggregating, by the software code executed by the hardware processor and using a second authoring criterion included in the compilation authoring data, the plurality of content items into a plurality of content subsets; grouping, by the software code executed by the hardware processor and using a third authoring criterion included in the compilation authoring data, at least some of the plurality of content subsets; obtaining, by the software code executed by the hardware processor, a dataset of compilation authoring data generated by a human editor; generating, by the software code executed by the hardware processor and using the trained machine learning model and the dataset, a compilation authoring template in an automated process; producing the content compilation, by the software code executed by the hardware processor and using the compilation authoring template, the at least some of the plurality of content subsets, and the consumption profile of the one or more end-users; computing, by the software code executed by the hardware processor, a desirability score predicting a desirability of the content compilation to the one or more end-users; and providing, by the software code executed by the hardware processor when the desirability score satisfies a predetermined threshold, the content compilation to the one or more end-users.