Curating narrative experiences through automated content compilation

Number: 12192583
Published: 2025-01-07
Filed: 2022-10-18
Assignee: Disney Enterprises, Inc.
Inventors: Eivy; Adam D. et al.
CPC: H04N21/4755; H04N21/8549; H04N21/466; H04N21/25883; H04N21/252; H04N21/8133; H04N21/4532; H04N21/25891
Verdict: Set aside narrative-content curation, 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 compilation authoring template generated using a trained-machine learning model and stored in the system memory, wherein the trained machine learning model is configured to generate the compilation authoring template implementing an editorial style of a human editor; and a software code stored in the system memory; the hardware processor configured to execute the software code to: obtain a plurality of content items from at least one content source; aggregate the plurality of content items, based on relevance to one another, into a plurality of content subsets, according to a respective one of a plurality of narrative stories of each of the plurality of content subsets; produce a content compilation, using the compilation authoring template and by concatenating the plurality of content subsets, to create a narrative experience having a narrative arc determined by a sequence in which the plurality of content subsets are combined to produce the content compilation; and provide the content compilation to one or more end-users. || 8. A method for use by a content compilation system including a computing platform having a hardware processor and a system memory storing a software code and a compilation authoring template generated using a trained machine learning model, wherein the trained machine learning model is configured to generate the compilation authoring template implementing an editorial style of a human editor, the method comprising: obtaining, by the software code executed by the hardware processor, a plurality of content items from at least one content source; aggregating, by the software code executed by the hardware processor, the plurality of content items, based on relevance to one another, into a plurality of content subsets, according to a respective one of a plurality of narrative stories of each of the plurality of content subsets; producing a content compilation, by the software code executed by the hardware processor, using the compilation authoring template and by concatenating the plurality of content subsets, to create a narrative experience having a narrative arc determined by a sequence in which the plurality of content subsets are combined to produce the content compilation; and providing, by the software code executed by the hardware processor, the content compilation to one or more end-users.