Method and System for Grading Media Based on User Actions
Publication Date: 2017-Oct-31
Publishing Venue
The IP.com Prior Art Database
The following operators can be used to better focus your queries.
( ) , AND, OR, NOT, W/#
? single char wildcard, not at start
* multi char wildcard, not at start
"..." literal
Examples:
(Cat? OR feline) AND NOT dog?
Cat? W/5 behavior
(Cat? OR feline) AND traits
Cat AND charact*
This guide provides a more detailed description of the syntax that is supported along with examples.
This search box also supports the look-up of an IP.com Digital Signature (also referred to as Fingerprint); enter the 72-, 48-, or 32-character code to retrieve details of the associated file or submission.
For a concept search, you can enter phrases, sentences, or full paragraphs in English. For example, copy and paste the abstract of a patent application or paragraphs from an article.
Concept search eliminates the need for complex Boolean syntax to inform retrieval. Our Semantic Gist engine uses advanced cognitive semantic analysis to extract the meaning of data. This reduces the chances of missing valuable information, that may result from traditional keyword searching.
The IP.com Prior Art Database
Undisclosed
English (United States)
1
Method and System for Grading Media Based on User Actions
Abstract
A method and system is disclosed for grading media based on user actions. The method and system automatically infers a user’s rating for a media item based on considering the implied/indirect actions of the user.
Description
Disclosed is a method and system for grading media based on user actions. The method and system automatically infers a user’s rating for a media item based on considering the implied/indirect actions of a user. The media item, can be, but need not be limited to, an audio song, an image, a slideshow, a video, an audio lecture. The implied/indirect actions of the user include, but need not be limited to, requesting an intelligent digital assistant of the user’s smart device to play a song, pausing or stopping a song from playing, the user liking a song after a time delay, adding a song to a collection and the like.
The method and system automatically infers a rank for the media item by analyzing the user’s actions corresponding to the media item. Further, the method and system implicitly monitors the user’s actions and augments the inferred ranking.
The inference takes into account the implied/indirect actions of the user, wherein the implied/indirect actions of the user include, but need not be limited to, the following:
Measuring the percentage of media coverage before the user expresses a like for the media item (such as the user liking the song 1% into its play versus at 70% of its play)
The user asking a digital assistant to play a song potentially including an elapsed time-based depreciation of impact
The user adding a media item to a collection (such as adding a song to a playlist) The user adding a media item for offline consumption (such as downloading a
song to listen to offline) The user adding a media item for offline consumption on multiple devices How often the user recalls a media item (such as asking home entertainment to
play song "X"), potentially including an elapsed time-based depreciation of impact
For example, if the user decided to tag a media item such as a song to a particular collection such as, Add song "Let's dance" to "Gym playlist", this action taken by the user indicates the user’s interest in the media item since the user chose to catalog the song for the user’s Gym playlist.
In another example, many media players/viewers allow the user to download a media item for previewing later. The user, taking this action, indicates the user’s interest in the
2
media item even if the user is not connected to the internet and irrespective of where the source of the media item is located. Also, if the user was to download the media item on multiple user devices, this action taken by the user indicates an even deeper level of user interest on the media item.
In yet another example, when a user frequently plays a particular song within a music player (whether it is from a single device or multiple devices), a level of frequency...