Patent Application
20210263983
This application relates generally to generating personalized entertainment content. The application relates more particularly to capture of a user's entertainment proclivities from their historic selections and interactions with entertainment content, and generating of new entertainment content relevant to the user.
Users interact with Internet web content on a daily basis. The Internet has evolved into a massive shopping venue. Many traditional brick-and-mortar shopping venues are disappearing as more purchases are done online. As to be expected, the Internet has also evolved into a major advertising arena. Sophisticated research engine sites monitor user interactions in order to determine what type of products or services might be of interest to them. Users are then subject to targeted advertising, and online retailers will pay the research engine site a fee when a user clicks on an advertisement stemming from targeted advertising. This model is specifically tailored for online retailers. User tastes or desires are monitored for the purpose of selling products.
Various embodiments will become better understood with regard to the following description, appended claims and accompanying drawings wherein:
The systems and methods disclosed herein are described in detail by way of examples and with reference to the figures. It will be appreciated that modifications to disclosed and described examples, arrangements, configurations, components, elements, apparatuses, devices methods, systems, etc. can suitably be made and may be desired for a specific application. In this disclosure, any identification of specific techniques, arrangements, etc. are either related to a specific example presented or are merely a general description of such a technique, arrangement, etc. Identifications of specific details or examples are not intended to be, and should not be, construed as mandatory or limiting unless specifically designated as such.
In accordance with example embodiments disclosed herein, systems and methods are taught to provide users with resources that are of specific personal interest to them. Unlike targeted advertising, as noted above, example embodiments target the interests of users, and not businesses. A user's taste in items such as music, television shows, movies, websites or streaming content is determined, and the user is provided with additional content that will allow the user to expand upon their interests.
Example embodiments herein aggregate a multitude of disparate, available user-to-entertainment-artifact interaction histories, determine an importance of the interactions, and select one or more of the top entertainment artifacts. The system then performs a multi-domain search and analysis utilizing natural language processing to find the most relevant multi-domain recommendations for each particular user. Examples include, but are not limited to Amazon merchandise, YouTube videos, streaming movies or shows, public events or gatherings, conventions, concert tickets, online articles, blogs, and the like.
The system specifically aims to expand the user's interests by way of recommending virtually anything which could be arrived at by Internet searches. It is not limited to things which are consumed online. It attempts to do the Internet searching work for the user that they would typically have to perform manually if the actively sought to expand their interests. Unlike recommendations from sites such as Amazon or Facebook or YouTube, it has a user-centric approach, not an advertisement-centric approach, and spans multiple domains.
In a further example embodiment, a mobile application allows a user to sync with as many accounts containing searchable entertainment-interactions as possible. A backend service is responsible for collecting data. Example information includes scrubbing Facebook “Like” data and posting habits, Amazon purchase history, Netflix/Hulu/Amazon viewing history, YouTube viewing history, online TV viewing history if available, and Internet browsing history, among others.
When initial entertainment artifacts are identified, relevant metadata is extracted from comments and interactions which are deemed positive by the natural language processor. Extracted metadata tags are stored and a multi-domain search with that metadata is completed with accounts linked to the app. For example, if a user has been watching a lot of nature and space documentaries on Netflix, there could be a public bird-watching or star-gazing Facebook event nearby with similar metadata that could be recommended.
When a user interacts with a recommendation, metadata tags are stored so as to be available for the next multi-domain search. This allows recommendations to get more specific as the user's interests evolve.
Natural language processing, when applied, assists in assuring that feedback on extracted content is positive, thus helping to refine the results. By linking a user's media accounts together, data can be extracted which targets that user's preferences across multiple domains. The provided domains can then be searched using tags extracted which are related to the user's preferences. When a user positively interacts with a recommendation from the system, metadata tags unique to this recommendation are extracted, stored and used to power a next set of recommendations. This allows recommendations to get more and more specific the more a user shows positive interactions and could allow the user to discover new interests.
In accordance with the subject application,
In the example embodiment of
Turning now to
Processor 304 is also in data communication with a storage interface 306 for reading or writing to a data storage system 308, suitably comprised of a hard disk, optical disk, solid-state disk, or any other suitable data storage as will be appreciated by one of ordinary skill in the art.
Processor 304 is also in data communication with a network interface controller (NIC) 330, which provides a data path to any suitable network or device connection, such as a suitable wireless data connection via wireless or wired network interface 338. A suitable data connection to a computing device or server is via a data network, such as a local area network (LAN), a wide arear network (WAN), which may comprise the Internet, or any suitable combination thereof. A digital data connection is also suitably directly with a computing device or server, such as via Bluetooth, optical data transfer, Wi-Fi direct, or the like.
Processor 304 is also in data communication with a user input/output (I/O) interface 340 which provides data communication with user peripherals, such as user input 342 and display 344 via display generator 346. Suitable user interfaces include touchscreens, as well as keyboards, mice, track balls, touch screens, or the like. It will be understood that functional units are suitably comprised of intelligent units, including any suitable hardware or software platform. Also in data communication with processor 304 is GPS interface 350.
While certain embodiments have been described, these embodiments have been presented by way of example only, and are not intended to limit the scope of the inventions. Indeed, the novel embodiments described herein may be embodied in a variety of other forms; furthermore, various omissions, substitutions and changes in the form of the embodiments described herein may be made without departing from the spirit of the inventions. The accompanying claims and their equivalents are intended to cover such forms or modifications as would fall within the spirit and scope of the inventions.
