Application (pre-grant publication)
TECHNIQUES FOR CURATING CONTENT ITEMS
- Number
- 20230156289
- Published
- 2023-05-18
- Filed
- 2021-11-12
- Assignee
- DISNEY ENTERPRISES, INC.
- Inventors
- Thaker; Madhav et al.
- CPC
- H04N21/44222; H04N21/4532; H04N21/4668; H04N21/4826
- Verdict
- Set aside content curation, business
- Source
- Google Patents · FreePatentsOnline
Abstract
Techniques are disclosed for curating content items. In some embodiments, a content item group generator applies rules defining inclusion and exclusion criteria to content items and associated metadata in order to assign the content items to content item groups. Given the assignments of content items to content item groups, a list generator applies a machine learning technique to generate, for each content item, a representation of the content item that includes weights associating the content item with the content item groups. The list generator then computes a weighted sum of representations of content items that a user has purchased and/or otherwise engaged with in order to generate a representation of the user that includes weights indicating affinities of the user with the content item groups. The list generator further generates one or more lists for display to the user based on the representation of the user.
Background
BACKGROUND Technical Field
Embodiments of the present disclosure relate generally to computer processing of content items and, more specifically, to techniques for curating content items. Description of the Related Art
As digital and mobile communications have become ubiquitous, there are increasingly many options for end users to enjoy media content in addition to the traditional options of watching broadcast television (TV) and watching movies in-theater. For example, end users can now stream free and subscription content to televisions or mobile devices, rent DVDs, purchase pay-per-view rights to specific digital content, and so on.
Currently, there are few techniques for organizing media content for consumption by end users. One conventional approach for organizing media content is to associate media content items with metadata that indicates generic categories to which the media content items belong. For example, a collection of movie titles could be associated with metadata indicating genres, such as “comedy,” “romance,” “science fiction,” etc. to which those movies titles belong. Lists of movie titles from the different genres can then be presented for consumption by an end user.
One drawback of the above approach is that multiple lists can include many of same media content items, because the metadata oftentimes indicates that each media content item belongs to more than one generic category. For example, the metadata could indicate multipl