Methods, systems, and apparatuses for facilitating content marketplaces

Abstract

Example implementations for facilitating content marketplaces are disclosed, which may comprise algorithms for determining one or more valuations for one or more media content, outputting a first media content of a first type from the one or more media content with an indication of a first valuation for the first media content from one or more valuations for the one or more media content, based on confirming a user directs his or her attention towards the outputted first media content, adjusting a credit count in a user profile for the user to reflect the valuation for the first media content, determining a second media content that is access-controlled, comparing the credit count in the user profile for the user to a second valuation for the second media content, and based on the credit count in the user profile satisfying the second valuation, granting access to the second media content.

Description

METHODS, SYSTEMS, AND APPARATUSES FOR FACILITATING CONTENT MARKETPLACESCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This patent claims the benefit of and priority to U.S. Provisional Application No. 63 / 663,791 filed June 25, 2024, and entitled “Methods, Systems, and Software for Cashless Content Experience Exchange.” U.S. Provisional Application No. 63 / 663,791 is hereby incorporated herein by reference in its entirety.FIELD OF THE DISCLOSURE

[0002] This disclosure relates generally to methods, systems, and apparatuses for facilitating content marketplaces.BACKGROUND

[0003] Media content, including digital media content, is often provided at a cost to a user or subscriber, or provided with costs covered by one or more advertisers. When media content is provided with its costs covered by one or more advertisers, the associated advertisements that accompany the media content are often distracting, ill placed, and ultimately degrade the experience of consuming the media content.BRIEF DESCRIPTION OF THE DRAWINGS

[0004] FIG. l is a flow diagram of illustrating operational flow in accordance with teachings of this disclosure.

[0005] FIG. 2 is a block diagram of a content manager in accordance with the teachings of this disclosure.

[0006] FIG. 3 is a flow diagram illustrating a valuation process capable of being performed by the content manager of FIG. 2 in accordance with the teachings of this disclosure.

[0007] FIG. 4 is a block diagram of a computing device used in accordance with the teachings of this disclosure.

[0008] Certain examples are shown in the above-identified figures and described in detail below. In describing these examples, like or identical reference numbers are used to identify the same or similar elements. The figures are not necessarily to scale and certain features andcertain views of the figures may be shown exaggerated in scale or in schematic for clarity and / or conciseness.

[0009] Unless specifically stated otherwise, descriptors such as “first,” “second,” “third,” etc., are used herein without imputing or otherwise indicating any meaning of priority, physical order, arrangement in a list, and / or ordering in any way, but are merely used as labels and / or arbitrary names to distinguish elements for ease of understanding the disclosed examples. In some examples, the descriptor “first” may be used to refer to an element in the detailed description, while the same element may be referred to in a claim with a different descriptor such as “second” or “third.” In such instances, it should be understood that such descriptors are used merely for identifying those elements distinctly that might, for example, otherwise share a same name.DETAILED DESCRIPTION

[0010] The digital content economy may draw consumers who are able and willing to pay for access to their choice of digital content as well as consumers who are not able and / or not willing to do the same. In examples where consumers are not able and / or not willing to pay for access to digital content, digital content providers may enable the consumption of digital content with advertising content at the beginning of the digital content, or with advertising content interspersed throughout the digital content. However, in each instance, the consumer may only passively consent to such advertising content in-so-much as the consumer is waiting for the digital content to begin or restart after the advertising content.

[0011] Additionally, the consumer may only passively watch the advertising content, if at all. Because of this, advertising campaigners frequently adopt a quantity over quality marketing plan with the hope that some subset of consumers to which advertising content is displayed will actually watch the advertisement, and then hoping that some subset of those consumers that actually watch the advertisement will act upon the advertisement (e.g., purchasing an advertised product or service). In some such examples, the advertising content may be short with only certain prioritized content delivered.

[0012] Consumers, however, often demand additional information before acting upon advertisements. Indeed, when advertising lacks deep content, consumers often have to seek out additional advertising content to obtain additional information, perform their own research on a service or product, or otherwise investigate the content within the advertising. This may place a burden on the consumer, which may ultimately curb potential sales.

[0013] The balance between supplying sufficient information to get a consumer to act on an advertisement versus maintaining consumer attention is a difficult problem in current systems. This is especially true where a consumer knows that other (e.g., non-advertising) content is set to begin or restart after the advertising content finishes.

[0014] Additionally, a consumer who seeks non-advertising content (e.g., watch a movie) may be distracted by interspersed, adjacent, or directly preceding advertising content. In examples such as virtual learning experiences, such distractions may have an extremely negative impact on a user’s learning experience, effectively altering the nature of the experience itself.

[0015] The systems, apparatuses, and methods described herein set forth a bifurcated system that provides both advertising and non-advertising content separately from each other. In some examples, at least one of the advertising or non-advertising content may be targeted to a user based on user demographics, user behavior data, user interests and / or user-supplied profile information, and / or specifics of content-consumption that may include the time, place, or pattern of such consumption, and / or user consents regarding user data. The systems, apparatuses, and methods described herein may analyze and determine valuations for each of the advertising and non-advertising content. The systems, apparatuses, and methods described herein enable users to, at a first time, acquire digital credits by consuming advertising content in accordance with the determined valuations associated therewith. At a second time, the user may be able to exchange accumulated digital credits to consume non-advertising content in accordance with the determined valuations associated therewith. In some such examples, the non-advertising content may be uninterrupted by the advertising content. In some such examples, the non-advertising content is copyrighted, private, or otherwise access-controlled content (e.g., behind a paywall). Examples, of non-advertising content includes video games, sports, music, movies, tv shows, video shorts, reels, snaps, articles, concerts, tutors, lecturers, continuing professional education, online courses, artificial intelligence chatbots, applications, sensory experiences generated through application of artificial intelligence, websites, navigation, streaming services, cellular communications, SMS / RCS messaging, subscriptions, memberships, etc.

[0016] As an example, a student may wish to learn about a particular topic but cannot afford a digital course or an Artificial Professor™ on that particular topic. The systems, apparatuses, and methods described herein may provide access to digital content about the particular topic based on credits accrued for watching or otherwise consuming advertising content. The systems, apparatuses, and methods described herein may establish an identifier and / or account for this student. The systems, apparatuses, and methods described herein may create a userprofile for the student that may include various demographics, behaviors, interests, historic analyses, etc. The systems, apparatuses, and methods described herein may select advertisement content that targets the student based on the user profile. In some examples, the systems, apparatuses, and methods described herein may query a user-data-to-first-content- match mechanism to select which content to serve to which user. In some examples, users may select advertisements to watch. In some such examples, the users may select advertisements based on the amount of credits that the systems, apparatuses, and methods described herein determine as valuable. For example, a political advertisement may be valued at 75 credits whereas a soap advertisement may be valued at 50 credits. The systems, apparatuses, and methods described herein may serve advertising content to the student and track its consumption by the user (e.g., ensuring that the advertising content was watched, rather than merely displayed). The systems, apparatuses, and methods described herein determine a numerical valuation corresponding to the consumption of the advertisement (e.g., 50 credits for watching a soap advertisement) and associate it with the student's identifier or profile or account. This process may be repeated, wherein the systems, apparatuses, and methods described herein accumulate additional numerical valuations (e.g., 75 credits for watching a political advertisement, which is then added to the initial 50 credits to accumulate to 125 credits).

[0017] Upon presentation with a correct amount of credits (e.g., 125 credits) by the user, the systems, apparatuses, and methods described herein may grant the user access to the digital course or the Artificial Professor™. The user may present his or her credits in exchange for access to the digital course at any time. In some examples, the user may transfer some or all of his or her credits to another user (a friend). The systems, apparatuses, and methods described herein may provide users access to digital content after one exchange (e.g., lump sum payment) or multiple exchanges (e.g., a subscription model). The systems, apparatuses, and methods described herein may provide users access to digital content only temporarily (e.g., daily, weekly, monthly, etc.).

[0018] The systems, apparatuses, and methods described herein may provide users access to digital content after confirming that a user has enough credits. In some examples, the systems, apparatuses, and methods described herein may use the valuation of the non-advertising content that a user is requesting as a minimum threshold (e.g., 100 pts minimum for accessing the astrophysics professor for a week). In some such examples, the systems, apparatuses, and methods described herein may compare the credits associated with the user to the minimum threshold and, if the credits associated with the user meet or exceed the minimum threshold,provide the user access. In some examples, credits associated with the user may be deducted upon the initial exchange. In some examples, the user may maintain their credits until the nonadvertising content is consumed (e.g., a given period of access lapsed, or a given number of Artificial Professor™ conversations took place).

[0019] The above can be repeated. The transfer of credits from one identifier to another can be repeated. While the above example describes a digital course or an Artificial Professor™, the systems, apparatuses, and methods described herein may provide users access to any digital content or experience. For example, a user may watch in one sitting all the advertisements that advertisers or content venues may expect to present to the user in a month. The user may accumulate a number of credits associated with those advertisements, which may subsequently be used to access desired content such as a movie stream (e.g., Amazon® Prime Video™), a month of a video-streaming platform (e.g., Netflix®), a month of an audio-streaming platform (e.g., Spotify®), a measure of access to a participatory digital experience (e.g., 25 minutes of a live-stream, five shots in a multi-player game), or the like.

[0020] The systems, apparatuses, and methods described herein may provide diversification of advertising formats and thus improved access to users by advertisers. An aspect of the systems, apparatuses, and methods described herein may be the exchange of a digital advertising experience for three-dimensional and / or haptic non-advertising experience such as a virtual and / or augmented reality experience, a composition of sensory experiences generated through application of artificial intelligence, etc.

[0021] In some examples, users may be able to pre-select access-controlled content that a user wants to consume, and the systems, apparatuses, and methods described herein may determine a number of digital credits required to access that content. The systems, apparatuses, and methods described herein may track (e.g., as a count or percentage of completion) as the user accumulates such digital credits to obtain access to such selected access-controlled content. In some such examples, a user may be informed of his or her progress towards acquiring access to one or more access-controlled content.

[0022] Thus, the systems, apparatuses, and methods described herein beneficially provide consumers with mechanisms to access otherwise access-controlled content through a marketplace exchange based on the users’ accumulation of separately consumed advertising content. Additionally, advertisers may benefit from more focused user attention on, and specific consent to consume, advertising content. In some such examples, advertisers may be able to develop more detailed and persuasive advertising content that may have a stronger impact on whether a user acts upon the advertisement.

[0023] The systems, apparatuses, and methods described herein may further facilitate the marketplace exchange described herein by adjusting valuations of content (both advertising and non-advertising content) depending on marketplace trends. For example, trending advertising content may be weighted lower than non-trending advertising content and trending non-advertising content may be weighted higher than non-trending non-advertising content. In some examples, content targeted to a user may be weighted lower than other non-targeted content. In some such examples, weighting trending advertising content and / or targeted content lower may avoid abuse of the system (e.g., abusing content exchange rates that provide maximum returns with minimum effort, otherwise known as min-maxing) and / or allow all content providers to benefit equally.

[0024] The systems, apparatuses, and methods described herein may receive from a user an indication of consent or intention to consume advertising content in exchange for access to non-advertising content. In some examples, the systems, apparatuses, and methods described herein may issue an identifier for a user. The systems, apparatuses, and methods described herein may gather at least one descriptor (e.g., demographic information, behavior information, interests, browsing history) related to the user and associate the at least one descriptor with the identifier of the user. In some examples, the systems, apparatuses, and methods described herein may create a user profile comprising the identifier of the user and the at least one descriptor.

[0025] Figure 1 illustrates an example operation process 100 in which a user of the systems, apparatuses, and methods described herein may be presented, or may locate, a first advertising content valued at a first number (e.g., X) of credits (step 102). In some examples, aspects of the user (e.g., user demographics, behaviors, interests, browsing history) may be used to locate the first advertising content. The user may watch or otherwise consume the first advertising content and the systems, apparatuses, and methods described herein may verify the user’s viewing or consumption of the first advertising content (e.g., eye tracking, frequent user input during presentation, quizzes, etc.).

[0026] At step 104, the systems, apparatuses, and methods described herein may update a credit count associated with the user with the first number of credits (e.g., user credit count + X credits) based on verification that the user watched or otherwise consumed the first advertising content. At some time thereafter (e.g., immediately, after a threshold of time, the next day, the next week, the next month, etc.), the user may be presented, or may request access to, non-advertising content valued at a second number (e.g., Y) of credits (step 106). At step 108, the systems, apparatuses, and methods described herein may compare the user credit countto the second number of credits. If the user credit count is not greater than or equal to the second number of credits (step 108: NO), then the process 100 may start over again at step 102 with a second advertising content valued at a third number (e.g., Z) of credits being presented to or located by the user. If the user credit count is greater than or equal to the second number of credits (step 108: YES), then the user may be able to obtain access to the non-advertising content by exchanging the second number (e.g., Y) of credits (e.g., the second number of credits may be deducted from the user credit count) at step 110. The process 100 may cease, repeat, or run continuously.

[0027] Figure 2 illustrates an example content manager 200 to implement the example process 100 described with reference to Figure 1. The example content manager 200 may comprise a user profile database 202, an advertising content database 204, a non-advertising content database 206, a content interface 208, a content valuator 210, and a content monitor 212.

[0028] The example user profile database 202 may store user profiles for any number of users. In some examples, the user profile database 202 stores user profiles, each of which may comprise a user identifier in association with user credits and user attributes, such as demographics, behaviors, interests, and / or historical use of the content manager 200. In some examples, the user profile database 202 may leverage certain attributes that advertisers already know about a user (e.g., browsing history, user demographic models based on previously disclosed information and / or expectations or analysis, census data, etc.). In some examples, a user may consent to supply additional information in its user profile to personalize his or her experience. For example, the content interface 208 may present input forms for which a user may supply additional information that may be stored in the user profile as, or to supplement, the user attributes.

[0029] The example advertising content database 204 may store one or more versions of advertising content for presentation to users in association with attributed valuations from the example content valuator 210. In some examples, advertising content in a first form may be associated with a first valuation (e.g., a standard version of the advertising content, which may be about 3 minutes, may be associated with a first valuation), the advertising content in a second form may be associated with a second valuation (e.g., a truncated version of the advertising content, which may be about 30 seconds, may be associated with a second valuation), and the advertising content in a third form may be associated with a third valuation (e.g., an extended version of the advertising content, which may be about 30 minutes, may be associated with a third valuation). In addition to multiple versions of the same advertising content, the example advertising content database 204 may store a plurality of different advertising content, each ofwhich may have its own version form (e.g., truncated, standard, and extended). In some such examples, the advertising content database 204 may enable a variety of advertising content of various lengths to be attributed a variety of valuations and accessed at a variety of times.

[0030] In some examples, an advertisement auction may be used to populate the advertising content database 204. For example, the content manager 200 may provide, to an advertisement auction, general information about users within the user profile database 202 as well as general information about the non-advertising content within the non-advertising content database 206. In some examples, the content manager 200 may provide, to the advertisement auction, specific information about users within the user profile database 202 as well as specific information about the non-advertising content within the non-advertising content database 206. In some examples, the content manager 200 may provide, to the advertisement auction, general information about users within the user profile database 202 as well as specific information about the non-advertising content within the non-advertising content database 206. In some examples, the content manager 200 may provide, to the advertisement auction, specific information about users within the user profile database 202 as well as general information about the non-advertising content within the non-advertising content database 206. In exchange, the advertisement auction may supply advertisements that are targeted towards the users of the content manager 200 and / or potential viewers of the non-advertising content.

[0031] In some examples the advertising content database 204 may handle the acquisition of advertisements from the auction in real-time. In some such examples, the advertising content database 204 may store the acquired advertising content in a temporarily (e.g., in a buffer).

[0032] The example non-advertising content database 206 may store one or more versions of non-advertising content for presentation to users in exchange for credits matching attributed valuations from the example content valuator 210. In some examples, non-advertising content in a first form may be associated with a first valuation (e.g., a lump sum for unrestricted access to the non-advertising content), the non-advertising content in a second form may be associated with a second valuation (e.g., temporary access associated with a pre-defined period of time such as, for example, daily, weekly, monthly access), the non-advertising content in a third form may be associated with a third valuation (e.g., pay-per-use), etc. In addition to multiple versions of the same non-advertising content, the example non-advertising content database 206 may store a plurality of different non-advertising content, each of which may have its own version forms (e.g., unrestricted, temporary, or pay-per-use access). In some examples, the non-advertising content database 206 may be populated with copyrighted or other access- controlled content.

[0033] The example content interface 208 may control interaction with users of the content manager 200. The content interface 208 may control user input (e.g., for content searching purposes, input forms, requesting and obtaining consent for storage of user demographics or the marketing, distribution, selling, re-selling, etc. of user content-consumption data to third- parties, and the like) and selection (e.g., selecting advertising and non-advertising content). For example, content interface 208 may receive data, such as demographics or interests, from a user (e.g., via one or more input forms) during user registration. The example content interface 208 may determine a unique identifier (ID) for the user and create a user profile based on the unique ID, received data and demographics, interests, behaviors, historical data, as well as a credit counter (e.g., initialized at zero). The content interface 208 may store the user profile, including the unique ID, received data, demographics, interests, behaviors, historical data, and credit counter, within the user profile database 202. In some examples, the content interface 208 may update the credit counter associated with the unique ID in the user profile database 202 as the user acquires, accumulates, and spends credits while using the content manager 200.

[0034] The content interface 208 may further control presentation of content to users via user displays (e.g., via one or more application windows, webpages, etc.). In some examples, the content interface 208 may present one or more advertising content separately from one or more non-advertising content. For example, the content interface 208 may display a first webpage or application window specific to advertising content. A user may, via the first webpage or application window, be presented or select one of the advertising content to consume. In some examples, the one or more advertising content may be presented in a list or table with or without pictorial thumbnails in the first webpage or application window.

[0035] In some examples, the content interface 208 may select a first advertising content of the one or more advertising content for a user. In some examples, the first advertising content may be targeted to a particular user based on general and / or specific information about the user. For example, the one or more advertising content may be targeted towards a group of users based on general information, and the first advertising content of the one or more advertising content may be targeted towards a particular user based on specific information. In some examples, the content interface 208 may determine the one or more advertising content based on general information known about the user from other sources (e.g., Google®, Facebook®, Instagram®, etc.). In some such examples, the content interface 208 may determine the first advertising content from the one or more advertising content based on specific informationfound within the user profile for that user stored within the user profile database 202 (which may not be found from the other sources).

[0036] The content interface 208 may display a second webpage, application window, or sensory interface specific to non-advertising content. In some examples, the second webpage, application window, or sensory interface may be separate from the first webpage, application window, or sensory interface so that non-advertising content is substantially separated from advertising content. A user may, via the second webpage, application window, or sensory interface, be presented or select one of the non-advertising content to consume. In some examples, the one or more non-advertising content may be presented in a list or table with or without pictorial thumbnails in the second webpage, application window, or other sensory interface.

[0037] In some examples, the one or more non-advertising content may be targeted to a particular user based on general and / or specific information about the user. For example, the one or more non-advertising content may be targeted towards a group of users based on general information, and a first non-advertising content of the one or more non-advertising content may be targeted towards a particular user based on specific information. For another example, the content interface 208 may trigger and / or direct the generation of bespoke non-advertising content addressing at least one characteristic associated with the user through employment of artificial intelligence technology. In some examples, the content interface 208 may determine the one or more non-advertising content based on general information known about the user from other sources. In some such examples, the content interface 208 may determine the first non-advertising content from the one or more non-advertising content based on specific information found within the user profile for that user stored within the user profile database 202.

[0038] The content interface 208 may further control the transfer of user credits between users (e.g., user l id credit count = user l id credit count - A & user_2_id credit count = user_2_id credit count + A), the accumulation of credits to a user profile based on consumption of advertising content (user l id credit count = user l id credit count + A), and a deduction of credits from a user profile based on consumption of non-advertising content (user l id credit count = user l id credit count - A).

[0039] The example content valuator 210 may analyze either one or both of advertising content and non-advertising content and determine a valuation to attribute to such content. In some examples, the example content valuator 210 may value advertising and non-advertising content according to the traditional costs for such materials (e.g., using a currency exchange model toassociate cost of content to credits). In some examples, the example content valuator 210 may value advertising and non-advertising content according to a weighted formula based on a number of variables. In some examples, the variables may include general user demographics, specific user demographics found within user profiles stored within the user profile database 202, user behavior data, user historical data (browsing history, historical use of content manager 200, etc.), user interests, current trends, discounts or promotions, advertiser goals, and / or user goals. In some examples, the variables may include specifics of the consumption of non-advertising and / or of advertising content such as the geography, time, speed, frequency, duration, pattern, etc. of such content consumption. In some examples, the variables may include specifics of the content, whether non-advertising or advertising content, such as the origination, source, licensing, etc. associated with the content (e.g., advertiser, creator, auction, network, etc.), how content is created (e.g., artificial intelligence, statistical modeling / deduction / induction, human agency, combination of human and machine agents, bespoke, real time, etc.), how content is delivered and / or experienced (e.g., asynchronously / synchronously, passively, through participation, etc.), the versioning of content (e.g., conversational learning with access to tiered-level databases of knowledge units), etc. In some examples, the variables may include the specifics of user consent with respect to user-associated data. For example, if / when a user grants consent to the storage of the user's demographic data, then the content valuator 210 may weight the credits that the user earns for the consumption of advertising content higher than, and / or may weight the valuation of the non-advertisement content to be served to the user lower than, when such consent is not granted. Similarly, if / when a user consents to the marketing, distribution, selling, re-selling, etc. of their content-consumption data to third-parties, the content valuator 210 may accordingly alter one or more content valuations associated with the user. In some such examples, the content valuator 210 may valuate passive real-time access to a digital map at 20 credits, valuate interactive access to the same map at 40 credits, valuate access to an interactive and remotely-storable version of the same map at 100 credits when the user does not consent to the sharing of the user's interaction with said map but valuate the same at 50 credits when the user consents to the user's data being stored and / or sold to third-parties.) In some examples, the example content valuator 210 may attribute weights to one or more (or all) of the variables in determining a valuation for a particular advertising or non-advertising content.

[0040] In some examples, the content valuator 210 may weight a demographic variable higher if the general demographics of a user (e.g., age, sex, income, state / country, pet owner, etc.) align with a particular advertising content or non-advertising content (e.g., to incentivize a userto consume advertising or non-advertising content that a user may find appealing). In some examples, the content valuator 210 may weight a demographic variable higher if the general demographics of a user do not align with a particular advertising content or non-advertising content (e.g., to incentivize a user to consume advertising or non-advertising content that a user would otherwise not find appealing).

[0041] In some examples, the content valuator 210 may weight a specific user demographic variable higher if a specific demographic of a user (e.g., student, parent, homeowner, renter, village / city, neighborhood, pool owner, dog owner, etc.) found within a user profile within the user profile database 202 aligns with a particular advertising content or non-advertising content (e.g., to incentivize a user to consume advertising or non-advertising content that a user may find very appealing). In some examples, the content valuator 210 may weight a demographic variable higher if the content-consumption patterns associated with a user do not align with a particular advertising content or non-advertising content (e.g., to incentivize a user to consume advertising or non-advertising content that a user would otherwise not find very appealing).

[0042] In some examples, the content valuator 210 may weight a user behavior variable higher if user behavior data (e.g., user buys soap every week) implies a user may act upon an advertisement aligning with that user behavior (e.g., to incentivize a user to buy a particular brand of soap).

[0043] In some examples, the content valuator 210 may weight a user history variable higher is user historical data (e.g., user switched from searching for cars to the content manager 200) implies a user may act upon an advertisement aligning with the user historical data (e.g., to further assist in the car search of the user).

[0044] In some examples, the content valuator 210 may weight a user interest variable higher if a specific interest of a user (e.g., snowboarding) aligns with an advertisement (e.g., a ski resort, new bindings, snowboarding goggles, etc.). In some examples, the content valuator 210 may weight a trending non-advertising content higher to require additional credits due the popularity of the non-advertising content. In some examples, the content valuator 210 may weight a trending advertising content lower to incentivize users to explore other advertising content.

[0045] In some examples, the content valuator 210 may weight advertising or non-advertising content lower due to discounts or promotions (e.g., in view of sales advertising or to incentivize consumption of uncommonly consumed non-advertising content). In some examples, the content valuator 210 may weight advertising content according to advertiser goals (e.g., increased weight to reach the widest amount of people, decreased weight to deemphasize poorperforming campaigns) or content provider goals (e.g., decreased weight to reach the widest amount of people, increased weight to deemphasize poor performing non-advertising content). In some examples, the content valuator 210 may weight non-advertising content higher according to user goals (e.g., applying a higher weight for non-advertising content that a user has actually expressed interest in consuming or that a statistical model predicts the user to be interested in consuming).

[0046] In some examples, the content valuator 210 may weight variables according to fuzzy logic, wherein the weighting may be on a scale between zero and one depending on a degree of similarity between metadata associated with advertising or non-advertising content and user data (e.g., demographics, user behavior data, user interests, and / or user-supplied profile information). For example, if a user illustrates a disinterest in snowboarding, but an interest in skateboarding, the content valuator 210 may weight an advertising content associated with snowboarding at 0.1, weight an advertising content associated with skateboarding at 0.9, and weight an advertising content associated with surfing somewhere therebetween (e.g., 0.7 due to surfing being similar to snowboarding and skateboarding, but generally performed in warmer climates).

[0047] The example content monitor 212 may monitor user consumption of advertising content to ensure that users actually consume the advertising content. The example content monitor 212 may also monitor user consumption of non-advertising content to determine if and when to deduct credits from a user profile associated with the user. In some examples, the content monitor 212 may implement eye tracking software in combination with one or more device cameras and / or other data-collecting apparatuses (for which the user may consent to their use) to ensure that a user is directing attention to outputted advertising (or non-advertising) content. In some examples, the one or more device cameras and / or other data-collecting apparatuses may be disposed on a user mobile device or computer running an instance of the content manager 200 via an application or via an Internet browser. In some examples, the one or more device cameras and / or other data-collecting apparatuses may be disposed on a dedicated device (e.g., a device that exclusively runs the content manager 200). In some examples, the content monitor 212 may instruct the content interface 208 to display interactive quizzes or checkpoints or other means of soliciting input to the user to confirm the user is engaged with the advertising (or non-advertising) content. In some examples, a user may be given multiple cues to direct his or her attention to the advertising content (e.g., three strikes), before the advertising content restarts or the credits attributed to consuming the advertising content are voided. In some examples, the content monitor 212 may instruct the content interface 208 to display aninteractive quiz at the end of the advertising content and a user may only acquire the credits attributed to the advertising content if the user receives a score above a certain threshold (e.g., at least 80% of quiz questions answered correctly). If the content monitor 212 determines that a user has directed his or her attention towards a respective advertising content, then the content monitor 212 may instruct the content interface 208 to adjust the profile of the user (and the credit counter) to reflect the addition of credits corresponding to the credits attributed to that advertising content.

[0048] In some examples, the content monitor 212 may perform similar determinations for a user consuming non-advertising content. For example, if the content monitor 212 determines that a user has directed his or her attention towards a respective non-advertising content, then the content monitor 212 may instruct the content interface 208 to adjust the profile of the user (and the credit counter) to reflect the subtraction of credits corresponding to the credits attributed to that non-advertising content. Alternatively, the content interface 208 may deduct credits from the profile of the user prior to the user directing his or her attention towards the non-advertising content. In some such examples, the content monitor 212 may determine whether a user has directed his or her attention towards the non-advertising content for other reasons such as collecting data on non-advertising content trends, time to complete content consumption, potential refunds for unconsumed content, etc.

[0049] In some examples, the content monitor 212 may monitor or track progress of a user towards unlocking one or more non-advertising content through the consumption of one or more advertising content. For example, a user may wish to consume a non-advertising content valued at X credits. To get to X credits, the user may opt to consume a first advertising content valued at A credits, a second advertising content valued at B credits, and a third advertising content valued at C credits. In some such examples, the content monitor 212 may temporally track the consumption by the user after each advertising content is consumed. For example, at a first time, the content monitor 212 may track that a user has accrued / consumed no credits out of X credits (e.g., 0 / X). At a second time, the content monitor 212 may track that a user has accrued / consumed A credits out of X credits (e.g., A / X after consuming the first advertising content). At a third time, the content monitor 212 may track that a user has accrued / consumed A+B credits out of X credits (e.g., A+B / X after consuming the second advertising content). At a fourth time, the content monitor 212 may track that a user has accrued / consumed A+B+C credits out of X credits (e.g., A+B+C / X after consuming the third advertising content). The content monitor 212 may instruct the content interface 208 to present this credit tracking to the user at various times and places (e.g., after the user finishes consuming an advertising content,within a webpage, application window, or interface dedicated to the user profile, when the user selects the non-advertising content, on all webpages, application windows, or interfaces, etc.).

[0050] In some examples, the content monitor 212 may update user profiles based on monitored use of the content manager 200 over time. For example, the content monitor 212 may update a user profile based on a user selection of a particular non-advertising content that the user wishes to consume. The content monitor 212 may determine that a particular nonadvertising content is of interest to that user and may update the user profile of that user to enable the content manager 212 to target future advertising and / or non-advertising content to the user.

[0051] In operation, (similarly as described above with reference to Figure 1) a user of the content manager 200 may interact with the content interface 208 to first register and acquire a unique ID. Thereafter, the content interface 208 may present, or the user may select, one or more advertising content from the advertising database 204 to the user, with each advertising content associated with a credit valuation determined by the content valuator 210. Upon selection by the user, or upon presentation of the one or more advertising content to the user by the content interface 208, the content monitor 212 may track consumption, by the user, of the one or more advertising content (e.g., for X credits). Based on consumption verification by the content monitor 212, the content interface 208 may update the user profile of the user within the user profile database 202 to reflect the accumulation of credits attributed to the one or more advertising content consumed by the user (user credit count + X credits). Thereafter, the content interface 208 may present, or the user may select, one or more non-advertising content from the non-advertising content database 206, with each non-advertising content associated with a credit valuation determined by the content valuator 210 (e.g., for Y credits). If the user profile of the user does not reflect sufficient credits to consume the one or more nonadvertising content, the content interface 208 may deny the user access to the one or more nonadvertising content, and the user may select (or the content interface 208 may present) additional advertising content. If the user profile of the user does reflect sufficient credits to consume the one or more non-advertising content, then the content interface 208 (and / or the content monitor 212) may grant access to the one or more non-advertising content. The content interface 208 may update the user profile of the user within the user profile database 202 to reflect the deduction of credits attributed to the one or more non-advertising content consumed by the user.

[0052] Figure 3 illustrates an example valuation process 300 to be performed by the content valuator 210 of Figure 2. The example valuation process 300 may begin with the contentmanager 200 receiving one or more media content (step 302). In some examples, the one or more media content may be advertising content and / or non-advertising content. For each received media content, the content valuator 210 may determine whether the media content is targeted to a demographic (step 304). If the content valuator 210 determines that the media content is not targeted to a demographic (step 304: NO), the content valuator 210 may attribute a first value to the media content according to a standard cost of that content (step 306). For example, if an online course costs $5000, the content valuator 210 may determine, via a currency exchange model, a number of credits to equal or to approximate $5000. Likewise, an advertisement may be valued according to its auction price. If the content valuator 210 determines that the media content is targeted to a demographic (step 304: YES), the content valuator 210 may compare the targeted demographic user profiles within the user profile database 202 (step 308). At step 310, the content valuator 210 may attempt to find users matching the targeted demographic. If the content valuator 210 does not find the user matching the target demographic (step 310: NO), control returns to step 306. If the content valuator 210 does find a user matching the target demographic (step 310: YES), an accountant valuator 210 may attribute a second value to the media content. In some examples, the second value may be equivalent to a value that an advertising auction may associate with a particular targeted advertisement for a particular targeted demographic (step 312). After either step 306 or step 312, the example content valuator of 210 may add a particular media content to a plurality of media content to be associated with the particular user (step 314). In some examples, the plurality of media content associated with the particular user may be stored in the advertising content database 204. After step 314 the for loop may end or otherwise repeat for each received media content.

[0053] After each piece of received media content has been analyzed according to user demographics (such as general demographics known to advertising auctions or other sources like Google®, Facebook®, Instagram®, etc.), the example content valuator 210 may compare the plurality of media content associated for a particular user to the user profile associated with that particular user within the user profile database 202 (step 316). In some examples, the content valuator 210 may search for user profile data that is similar to metadata associated with the plurality of media content (step 318). Example metadata associated with a plurality of media content may include, without limitation, topics, titles, subtitle information, actors, actresses, length of time, age restrictions, etc. In some examples, the content valuator 210 may also compare the plurality of media content to content trends in step 320. In some examples, step 318 and step 320 may be performed in parallel. In some examples, if the content valuator210 does not find a user profile with data similar to the media content metadata (step 318: NO), step 320 may be performed thereafter. If the content valuator 210 does find a user profile with data similar to metadata associated with the plurality of media content (step 318: YES), then the content valuator 210 may attribute a third value to each individual media content that matches the user profile data (step 322). In some examples the third value maybe greater than the second value, due to the increased specificity in the targeting of the media content to that particular user.

[0054] In some examples the content valuator 210 may determine, based on its comparison of the plurality of media content to content trends, whether or not a media content is trending (step 324). If a particular media content is not trending (step 324: NO), then the content valuator 210 may adjust the attributed value for that particular media content in a first direction (step 326). In some examples, the first direction may be an increase in value, such as for nontrending advertising content. In some examples, the first direction may be a decrease in value, such as for non-trending non-advertising content.

[0055] If the particular media content is trending (step 324: YES), then the content valuator 210 may adjust the attributed value for that particular media content in a second direction (step 328). In some examples the second direction may be a decrease in value, such as for trending advertising content. In some examples, the second direction may be an increase in value, such as trending non-advertisement content. After either step 326 or step 328, the example content valuator 210 may determine whether to discount, surge, or maintain the value of a particular immediate content (step 330). In some examples, the content valuator 210 may determine to discount a media content (e.g., lower its value), surge a media content (e.g., raise its value), or maintain the value of the media content based on statistical analyses, advertising or content provider sales or incentives, or the like. In some examples, media content of a particular type may be valued higher (e.g., an advanced quantum physics course may be valued higher than an intro to art history) and thus may be increased at step 330. At step 332, the content valuator 210 may associate to the received media content whatever is the attributed value after performance of process 300. The attributed value may be stored in association with advertising content in the advertising content database 204, or stored in association with non-advertising content in the non-advertising content database 206. The process 300 may be repeated as new media content is received or at any time. In some examples, the process 300 may run / repeat continuously for various users and media content. In some examples, based on the process 300, a first user may be presented with media content (both advertising and non-advertising) that are valued differently from that of a second user. For example, two users may acquiredifferent numbers of credits for consuming the same advertising content. In some examples, two users seeking to consume the same non-advertising material may have to consume different numbers or types of advertising content, of consume the same advertising content for different (longer / shorter) periods of time (e.g., one user may acquire X credits consuming a truncated version of a first advertising content, whereas another user may have to consume an extended version of the first advertising content to acquire the same X credits).

[0056] Figure 4 illustrates an example computing device 400 that may be used in accordance with the teachings described herein. The example computing device 400 may be a computer, a tablet, a mobile device, a server, a workstation, an internet-of-things (loT) device, a smart appliance, a network node, a hub, a router, a modem, AR / VR and haptic devices, other devices communicating with cloud-based or fixed backend computing resources, or the like. The example computing device 400 may comprise one or more processing units 402, one or more memory 404, one or more input devices or sensors 406, one or more output devices 408, one or more input / output (I / O) and communication interfaces 410, one or more programming interfaces 412, and one or more storage devices 414. Each of the one or more processing units 402, one or more memory 404, one or more input devices or sensors 406, one or more output devices 408, one or more input / output (I / O) and communication interfaces 410, one or more programming interfaces 412, and one or more storage devices 414 may be interconnected via wired connections such as, for example, a bus 416.

[0057] Alternatively, each of the one or more processing units 402, one or more memory 404, one or more input devices or sensors 406, one or more output devices 408, one or more input / output (I / O) and communication interfaces 410, one or more programming interfaces 412, and one or more storage devices 414 may be interconnected wirelessly. In some examples, each of the one or more processing units 402, one or more memory 404, one or more input devices or sensors 406, one or more output devices 408, one or more input / output (I / O) and communication interfaces 410, one or more programming interfaces 412, and one or more storage devices 414 may be interconnected via a combination of wired and wireless connections. In some examples, the example computing device 400 may be connected to one or more external servers 418. The components of the computing device 400 may be configured as a single device or multiple interdependent or stand-alone devices in close proximity and / or distributed over geographically remote areas.

[0058] In some examples, the processing unit 402 may be a processor such as a central processing unit (CPU), an Accelerated Processing Unit (“APU”), a microprocessor, an integrated circuit (IC), an application-specific integrated circuit (ASIC), a Field ProgrammableGate Array (FPGA), or a graphical processing unit (GPU). In some examples, the computing device 400 may have one or more processing units 402 for parallel processing. In some such examples, the one or more processing units 402 may be of the same type (e.g., multiple microprocessors). In some examples, the one or more processing units 402 may be of different types (e.g., at least one CPU and at least one GPU). The processing unit 402 may contain cache memory units for temporary local storage of instructions, data, or computer addresses. The processing unit 402 may be implemented as a single-chip, multiple chips and / or other electrical components including one or more integrated circuits and printed circuit boards that implements and executes logic in hardware, in addition to executing software.

[0059] In some examples, the memory 404 may be a non-transitory computer readable storage medium. In some examples, the memory 404 may include random-access memory, such as DRAM, SRAM, DDR RAM, or other random-access solid-state memory devices. In some examples, the memory 404 may comprise Read Only Memory (“ROM”), and / or another type of dynamic or static storage device, such as flash, magnetic, and optical memory, etc. that stores information and / or instructions for use by the processing units 402. The memory 404 may include one or more memory cards that may be loaded on a temporary or permanent basis. The memory 404 and / or the storage devices 414 may include a Subscriber Identification Module (“SIM”) card and reader.

[0060] In some examples, the memory 404 may include an operating system 420 and instructions 422. The operating system 420 may be a traditional operating system that relies on pre-defined rules and structures such as, for example, Microsoft Windows®, Linux, macOS, etc. In some examples, the operating system 420 may be an adaptive, self-modifying, and dynamic operating environment powered by the generative neural networks described herein. In some examples, the operating system 420 may adapt and learn using generative neural networks, which may allow the operating system 420 to evolve and improve over time, responding to the specific needs and preferences of users. In some examples, the operating system 420 may have a generative user interface (UI), which may not be fixed or predetermined and instead may be generated dynamically based on users’ actions, needs, and preferences. The generative UI may be able to change and adapt in real-time and may provide an intuitive and efficient experience for users. In some examples, the operating system 420 may learn from each user’s behaviors and / or preferences to create an interface that may be tailored specifically to him / her. The operating system 420 may be able to function effectively on a wide range of devices and platforms including smartphones, tablets, desktops, servers, etc. In someexamples, the operating system 420 may be decentralized, such that users may share resources and may collaborate without reliance on centralized servers.

[0061] The processing unit 402 may connect to other computer systems and / or to telecommunications networks as part of performing one or more steps of one or more processes described or illustrated herein, according to particular needs. This can be accomplished through APIs or other methods, using FHIR format or other health-specific format. The computing device 400 may implement processes employing hardware and / or software to provide functionality via hardwired logic or otherwise embodied in circuits, such as integrated circuits, which may operate in place of or together with software to execute one or more processes or one or more steps of one or more processes described or illustrated herein. Software implementing particular embodiments may be written as instructions 422 in any suitable programming language (e.g., procedural, object oriented, etc.) or combination of programming languages, where appropriate. The instructions 422 may comprise computer executable instruction sets for implementing one or more steps of one or more processes 100, 300 described and illustrated in Figures 1 and 3. In addition, or as an alternative, one or more steps of one or more processes described or illustrated herein for execution in one processor may be executed at multiple CPUs that are local or remote from each other across one or more networks.

[0062] In some examples, the one or more input devices or sensors 406 may comprise one or more image / video sensors (e.g., cameras), one or more accelerometers, one or more gyroscopes, one or more thermometers, one or more physiological sensors, one or more microphones, a signal receiver, a haptics engine, a gesture-recognition engine, one or more depth sensors, a keyboard, a numeric pad, a mouse, a touchscreen, a trackpad, track balls, buttons, switches, joy sticks, directional pads, transducers, card readers, voice and handwriting inputs, and various other sensors for sensing information such as biometrics, temperature & other environmental conditions, such as air quality, etc., location via Global Positioning System (“GPS”) or otherwise, accelerometer, gyroscope, compass, actuator data, or the like.

[0063] In some examples, the one or more output devices 408 may comprise one or more displays, one or more speakers, one or more lights (e.g., light emitting diodes), a signal generator, a haptics engine, a printer, other sensory devices, mechanical, or other electromagnetic digital or analog output, or the like.

[0064] In some examples, the one or more VO and communication interfaces 410 may comprise one or more transceivers, receivers, transmitters, modulators, demodulators that enable communication with other devices, via wired and / or wireless connections. Example VOand communication interfaces 410 include ethernet, optical, coaxial, Universal Serial Bus (“USB”), FIREWIRE, THUNDERBOLT, Infrared (“IR”), Radio Frequency (“RF”) including the various WI-FI, IEEE 802.3x, IEEE 802.1 lx, IEEE 802.16x, GSM, CDMA, TDMA, GPS, IR, BLUETOOTH, Bluetooth Low Energy (BLE), ZIGBEE, SPI, I2C, WiMax, cellular, WiFi Direct, SuperWiFi, 802.15.4, LTE systems, LTE Direct, past, current, and future cellular standard protocols, e.g., 4-5G, or other wireless signal protocols or technologies, or the like type interface.

[0065] In some examples, the one or more programming interfaces 412 may comprise software for implementing one or more physical I / O and communication interfaces, application programming interfaces (APIs) configured for communication with and providing services to databases, software applications, the Internet, or the like.

[0066] In some examples, the one or more storage devices 414 may comprise non-volatile memory, such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state storage devices. In some examples, the one or more storage devices 414 may include one or more databases including, for example, the user profile database 202, the advertising content database 204, and the non-advertising content database 206 of Figure 2. The one or more storage devices 414 may store information, instructions, and / or software. The one or more storage devices 414 may be used to store executables, data, applications, and the like, and may include fast access primary storage, as well as slower access secondary storage, which may be virtual or fixed. The one or more storage devices 414 may be configured to read one or more transitory and / or non-transitory computer-readable media that store or otherwise embody software implementing particular embodiments. A computer-readable medium may be any tangible medium capable of carrying, communicating, containing, holding, maintaining, propagating, retaining, storing, transmitting, transporting, or otherwise embodying software, where appropriate, including nano-scale medium. A computer-readable medium may be a biological, chemical, electronic, electromagnetic, infrared, magnetic, optical, quantum, or other suitable medium or a combination of two or more such media, where appropriate. Example computer-readable media include, but are not limited to fixed and removable drives, ASIC, Compact Disks (“CDs”), Digital Video Disks (“DVDs”), FPGAs, floppy disks, optical and magneto-optic disks, hard disks, holographic storage devices, magnetic tape, caches, Programmable Logic Devices (“PLDs”), RAM devices, ROM devices, semiconductor memory devices, solid state drives, cartridges, and other suitable computer-readable media.

[0067] The bus(es) 416 may connect a wide variety of other subsystems, in addition to those depicted, and may include various other components that permit communication among the components in the computing resources. The bus(es) 416 may encompass one or more digital signal lines serving a common function, where appropriate, and various structures including memory, peripheral, or local buses using a variety of bus architectures. Example bus(es) 416 may comprise an Industry Standard Architecture (“ISA”) bus, an Enhanced ISA (“EISA”) bus, a Micro Channel Architecture (“MCA”) bus, a Video Electronics Standards Association Local Bus (“VLB”), a Peripheral Component Interconnect (“PCI”) bus, a PCI-eXtended (“PCI-X”) bus, a Peripheral Component Interconnect Express (PCIe) bus, a Controller Area Network (“CAN”) bus, and an Accelerated Graphics Port (“AGP”) bus.

[0068] In some examples, the one or more external servers 418 may be remote computing devices to support the computing device 400. In some examples the one or more external servers 418 may be remote versions of the computing device 400 that may provide redundancies (e.g., back up storage, databases, software, operating systems, processors, etc.). In some examples, the one of more external servers 418 may provide a centralized hub for managing a plurality of computing devices 400. In some examples, the one or more external servers 418 may enable cloud computing for the processes described herein.

[0069] As used herein, the term component is intended to be broadly construed as hardware, firmware, and / or a combination of hardware and software. It will be apparent that systems and / or methods, described herein, may be implemented in different forms of hardware, firmware, or a combination of hardware and software. The actual specialized control hardware or software code used to implement these systems and / or methods is not limiting of the implementations. Thus, the operation and behavior of the systems and / or methods were described herein without reference to specific software code— it being understood that software and hardware can be designed to implement the systems and / or methods based on the description herein.

[0070] Certain user interfaces have been described herein and / or shown in the figures. A user interface may include a graphical user interface, a non-graphical user interface, a text-based user interface, etc. A user interface may provide information for display. In some implementations, a user may interact with the information, such as by providing input via an input component of a device that provides the user interface for display. In some implementations, a user interface may be configurable by a device and / or a user (e.g., a user may change the size of the user interface, information provided via the user interface, a position of information provided via the user interface, etc.). Additionally, or alternatively, a userinterface may be pre-configured to a standard configuration, a specific configuration based on a type of device on which the user interface is displayed, and / or a set of configurations based on capabilities and / or specifications associated with a device on which the user interface is displayed.

[0071] Some implementations are described herein in connection with thresholds. As used herein, satisfying a threshold may refer to a value being greater than the threshold, more than the threshold, higher than the threshold, greater than or equal to the threshold, less than the threshold, fewer than the threshold, lower than the threshold, less than or equal to the threshold, equal to the threshold, etc.

[0072] The foregoing disclosure provides examples, illustrations and descriptions of the present invention, but is not intended to be exhaustive or to limit the implementations to the precise form disclosed. Modifications and variations are possible in light of the above disclosure or may be acquired from practice of the implementations. These and other variations and modifications of the present invention are possible and contemplated, and it is intended that the foregoing specification and the following claims cover such modifications and variations.

[0073] Even though particular combinations of features are recited in the claims and / or disclosed in the specification, these combinations are not intended to limit the disclosure of possible implementations. In fact, many of these features may be combined in ways not specifically recited in the claims and / or disclosed in the specification. Although each dependent claim listed below may directly depend on only one claim, the disclosure of possible implementations includes each dependent claim in combination with every other claim in the claim set.

[0074] No element, act, or instruction used herein should be construed as critical or essential unless explicitly described as such. Also, as used herein, the articles "a" and "an" are intended to include one or more items and may be used interchangeably with “at least one” or "one or more”. Furthermore, as used herein, the term "set" is intended to include one or more items and may be used interchangeably with “at least one” or "one or more." Where only one item is intended, the term "one" or similar language is used. Also, as used herein, the terms "has," "have," "having," or the like are intended to be open-ended terms. Further, the phrase "based on" is intended to mean "based, at least in part, on" unless explicitly stated otherwise.

[0075] The presence or absence of a summary, abstract, or claims in this application should in no way be considered as limiting on the scope of any inventions disclosed herein.

[0076] As used herein, the terms “substantially” and / or “approximately” modify their subjects and / or values to recognize the potential presence of variations that occur in real world applications. For example, “substantially” and / or “approximately” may modify dimensions that may not be exact due to manufacturing tolerances and / or other real-world imperfections as will be understood by persons of ordinary skill in the art. For example, “substantially” and / or “approximately” may indicate such dimensions may be within a tolerance range of + / - 10% unless otherwise specified in the description provided herein.

[0077] As used herein, the terms “including” and “comprising” (and all forms and tenses thereof) are open-ended terms. Thus, whenever the written description or a claim employs any form of “include” or “comprise” (e.g., comprises, includes, comprising, including, having, etc.) as a preamble or within a claim recitation of any kind, it is to be understood that additional elements, terms, etc., may be present without falling outside the scope of the corresponding claim or recitation.

[0078] As used herein, singular references (e.g., “a,” “an,” “first,” “second,” etc.) do not exclude a plurality. The term “a” or “an” object, as used herein, refers to one or more of that object. The terms “a” (or “an”), “one or more,” and “at least one” are used interchangeably herein. Furthermore, although individually listed, a plurality of means, elements, or method actions may be implemented by, for example, the same entity or object. Additionally, although individual features may be included in different examples or claims, these may possibly be combined, and the inclusion in different examples or claims does not imply that a combination of features is not feasible and / or advantageous.

[0079] The term “and / or” when used, for example, in a form such as A, B, and / or C refers to any combination or subset of A, B, C such as (1) A alone, (2) B alone, (3) C alone, (4) A with B, (5) A with C, (6) B with C, or (7) A with B and with C.

[0080] As used herein, when the phrase “at least” is used as the transition term in, for example, a preamble of a claim, it is open-ended in the same manner as the term “comprising” and “including” are open-ended. As used herein in the context of describing structures, components, items, objects, and / or things, the phrase “at least one of A and B” is intended to refer to implementations including any of (1) at least one A, (2) at least one B, or (3) at least one A and at least one B. Similarly, as used herein in the context of describing structures, components, items, objects, and / or things, the phrase “at least one of A or B” is intended to refer to implementations including any of (1) at least one A, (2) at least one B, or (3) at least one A and at least one B. As used herein in the context of describing the performance or execution of processes, instructions, actions, activities, and / or steps, the phrase “at least one ofA and B” is intended to refer to implementations including any of (1) at least one A, (2) at least one B, or (3) at least one A and at least one B. Similarly, as used herein in the context of describing the performance or execution of processes, instructions, actions, activities, and / or steps, the phrase “at least one of A or B” is intended to refer to implementations including any of (1) at least one A, (2) at least one B, or (3) at least one A and at least one B.

[0081] An example method comprises determining one or more valuations for one or more media content, wherein the valuations are based on weighting one of more variables comprising a type of the one or more media content, user general demographics, user specific demographics, user behaviors, user interests, and user browsing histories, outputting a first media content of a first type from the one or more media content with an indication of a first valuation for the first media content from one or more valuations for the one or more media content, monitoring the output of the first media content to confirm a user directs his or her attention towards the outputted first media content, based on confirming the user directs his or her attention towards the outputted first media content, adjusting a credit count in a user profile to reflect the valuation for the first media content, receiving a request, from the user, for a second media content of a second type, wherein the second type is access-controlled media content, and comparing the credit count in the user profile for the user to a second valuation for the second media content from one or more valuations for the one or more media content; and based on the credit count in the user profile for the user being equal to or greater than the second valuation, outputting the second media content.

[0082] Another example method comprises determining one or more valuations for one or more media content, wherein the valuations are based on weighting one of more variables comprising a type of the one or more media content, user general demographics, user specific demographics, user behaviors, user interests, and user browsing histories, outputting a first media content of a first type from the one or more media content with an indication of a first valuation for the first media content from one or more valuations for the one or more media content, monitoring the output of the first media content to confirm a user directs his or her attention towards the outputted first media content, based on confirming the user directs his or her attention towards the outputted first media content, adjusting a credit count in a user profile to reflect the valuation for the first media content, determining a second media content of a second type, wherein the second type is access-controlled media content, and comparing the credit count in the user profile for the user to a second valuation for the second media content from one or more valuations for the one or more media content; and based on the credit countin the user profile for the user being equal to or greater than the second valuation, outputting the second media content.

[0083] In some methods, based on the credit count in the user profile for the user being less than the second valuation, the method may further block access to the second media content, and output a third media content of the first type from the one or more media content with an indication of a third valuation for the third media content from one or more valuations for the one or more media content.

[0084] In some methods, the method may further determine the one or more valuations for one or more media content by weighting advertising media content higher when the advertising media content is not trending, when metadata associated with the advertising media content is similar to user general demographics, when the metadata associated with the advertising media content is similar to user specific demographics, when the metadata associated with the advertising media content is similar to user behaviors, when the metadata associated with the advertising media content is similar to user interests, and when the metadata associated with the advertising media content is similar to user browsing histories.

[0085] In some methods, the method may further determine the one or more valuations for the one or more media content by weighting the advertising media content according to fuzzy logic based on how similar the metadata associated with the advertising media content is to user general demographics, user specific demographics, user behaviors, user interests, and user browsing histories.

[0086] In some methods, the method may further determine the one or more valuations for one or more media content by weighting non-advertising media content higher when the nonadvertising media content is trending, when metadata associated with the non-advertising media content is similar to user general demographics, when the metadata associated with the non-advertising media content is similar to user specific demographics, when the metadata associated with the non-advertising media content is similar to user behaviors, when the metadata associated with the non-advertising media content is similar to user interests, and when the metadata associated with the non-advertising media content is similar to user browsing histories.

[0087] In some methods, the method may further determine the one or more valuations for the one or more media content by weighting the non-advertising media content according to fuzzy logic based on how similar the metadata associated with the non-advertising media content is to user general demographics, user specific demographics, user behaviors, user interests, and user browsing histories.

[0088] In some methods, the method may, based on outputting the second media content, adjust the credit count in the user profile to reflect the valuation for the second media content.

[0089] In some methods, the method may determine the first media content or the second media content based on to user general demographics, user specific demographics, user behaviors, user interests, and user browsing histories.

[0090] An example apparatus may comprise a content interface, a content valuator, and a content monitor to perform any of the above methods.

[0091] An example computer readable storage medium may store instructions that, when executed, cause performance of any of the above methods.

[0092] An example system may comprise one or more processors and memory storing instructions that, when executed by the one or more processors, cause performance of any of the above methods.

[0093] Although certain example apparatus, systems, methods, and articles of manufacture have been disclosed herein, the scope of coverage of this patent is not limited thereto. On the contrary, this patent covers all apparatus, systems, methods, and articles of manufacture fairly falling within the scope of the claims of this patent.

[0094] The following claims are hereby incorporated into this Detailed Description by this reference, with each claim standing on its own as a separate embodiment of the present disclosure.

Claims

What Is Claimed Is:

1. A system comprising: one or more processors; and memory storing instructions that, when executed by the one or more processors, cause the system to: determine one or more valuations for one or more media content, wherein the valuations are based on weighting one of more variables comprising a type of the one or more media content, user general demographics, user specific demographics, user behaviors, user interests, and user browsing histories; output a first media content of a first type from the one or more media content with an indication of a first valuation for the first media content from one or more valuations for the one or more media content; monitor the output of the first media content to confirm a user directs his or her attention towards the outputted first media content; based on confirming the user directs his or her attention towards the outputted first media content, adjust a credit count in a user profile to reflect the valuation for the first media content; receive a request, from the user, for a second media content of a second type, wherein the second type is access-controlled media content; compare the credit count in the user profile for the user to a second valuation for the second media content from one or more valuations for the one or more media content; and based on the credit count in the user profile for the user being equal to or greater than the second valuation, output the second media content.

2. The system of claim 1, wherein the instructions, when executed by the one or more processors, further cause the system to, based on the credit count in the user profile for the user being less than the second valuation: block access to the second media content; and output a third media content of the first type from the one or more media content with an indication of a third valuation for the third media content from one or more valuations for the one or more media content.

3. The system of claim 1, wherein the instructions, when executed by the one or more processors, cause the system to determine the one or more valuations for one or more media content by weighting advertising media content higher when the advertising media content is not trending, when metadata associated with the advertising media content is similar to user general demographics, when the metadata associated with the advertising media content is similar to user specific demographics, when the metadata associated with the advertising media content is similar to user behaviors, when the metadata associated with the advertising media content is similar to user interests, and when the metadata associated with the advertising media content is similar to user browsing histories.

4. The system of claim 3, wherein the instructions, when executed by the one or more processors, cause the system to determine the one or more valuations for the one or more media content by weighting the advertising media content according to fuzzy logic based on how similar the metadata associated with the advertising media content is to user general demographics, user specific demographics, user behaviors, user interests, and user browsing histories.

5. The system of claim 1, wherein the instructions, when executed by the one or more processors, cause the system to determine the one or more valuations for one or more media content by weighting non-advertising media content higher when the non-advertising media content is trending, when metadata associated with the non-advertising media content is similar to user general demographics, when the metadata associated with the non-advertising media content is similar to user specific demographics, when the metadata associated with the non-advertising media content is similar to user behaviors, when the metadata associated with the non-advertising media content is similar to user interests, and when the metadata associated with the non-advertising media content is similar to user browsing histories.

6. The system of claim 5, wherein the instructions, when executed by the one or more processors, cause the system to determine the one or more valuations for the one or more media content by weighting the non-advertising media content according to fuzzy logic based on how similar the metadata associated with the non-advertising media content is to the user general demographics, the user specific demographics, the user behaviors, the user interests, and the user browsing histories.

7. The system of claim 1, wherein the instructions, when executed by the one or more processors, further cause the system to, based on outputting the second media content, adjust the credit count in the user profile to reflect the valuation for the second media content.

8. An apparatus comprising: a content valuator configured to determine one or more valuations for one or more media content, wherein the valuations are based on weighting one of more variables comprising a type of the one or more media content, user general demographics, user specific demographics, user behaviors, user interests, or user browsing histories; a content interface configured to output a first media content of a first type from the one or more media content with an indication of a first valuation for the first media content from one or more valuations for the one or more media content; a content monitor configured to: monitor the output of the first media content to confirm a user directs his or her attention towards the outputted first media content; based on confirming the user directs his or her attention towards the outputted first media content, increase a credit count in a user profile according to the valuation for the first media content; and wherein the content interface is further configured to: determine a second media content of a second type, wherein the second type is access-controlled media content; compare the credit count in the user profile for the user to a second valuation for the second media content from one or more valuations for the one or more media content; and based on the credit count in the user profile for the user being equal to or greater than the second valuation, output the second media content.

9. The apparatus of claim 8, wherein the content interface is further configured to determine the first media content or the second media content based on the user general demographics, the user specific demographics, the user behaviors, the user interests, or the user browsing histories.

10. The apparatus of claim 8, wherein the content interface is further configured to, after outputting the second media content, deduct the credit count in the user profile according to the valuation for the second media content.

11. The apparatus of claim 8, wherein the content interface is further configured to, based on the credit count in the user profile for the user being less than the second valuation: block access to the second media content; and output a third media content of the first type from the one or more media content with an indication of a third valuation for the third media content from one or more valuations for the one or more media content.

12. The apparatus of claim 8, wherein the content valuator configured to determine the one or more valuations for one or more media content by: weighting advertising media content higher when the advertising media content is not trending, when metadata associated with the advertising media content is similar to user general demographics, when the metadata associated with the advertising media content is similar to user specific demographics, when the metadata associated with the advertising media content is similar to user behaviors, when the metadata associated with the advertising media content is similar to user interests, or when the metadata associated with the advertising media content is similar to user browsing histories; and weighting non-advertising media content higher when the non-advertising media content is trending, when metadata associated with the non-advertising media content is similar to user general demographics, when the metadata associated with the non-advertising media content is similar to user specific demographics, when the metadata associated with the non-advertising media content is similar to user behaviors, when the metadata associated with the non-advertising media content is similar to user interests, or when the metadata associated with the non-advertising media content is similar to user browsing histories.

13. The apparatus of claim 12, wherein the content valuator is further configured to determine the one or more valuations for the one or more media content by applying fuzzy logic to the weighting based on how similar the metadata associated with the advertising media content or the metadata associated with the non-advertising content is to the user generaldemographics, the user specific demographics, the user behaviors, the user interests, or the user browsing histories.

14. A computer readable storage medium storing instructions that, when executed, cause: determining one or more valuations for one or more media content, wherein the valuations are based on weighting one of more variables comprising a type of the one or more media content, user general demographics, user specific demographics, user behaviors, user interests, and user browsing histories; outputting a first media content of a first type from the one or more media content with an indication of a first valuation for the first media content from one or more valuations for the one or more media content; adjusting a credit count in a user profile to reflect the valuation for the first media content; receiving a request, from the user, for a second media content of a second type, wherein the second type is access-controlled media content; comparing the credit count in the user profile for the user to a second valuation for the second media content from one or more valuations for the one or more media content; and based on the credit count in the user profile for the user being equal to or greater than the second valuation, outputting the second media content.

15. The storage medium of claim 14, wherein the instructions, when executed, further cause, based on the credit count in the user profile for the user being less than the second valuation: blocking access to the second media content; and outputting a third media content of the first type from the one or more media content with an indication of a third valuation for the third media content from one or more valuations for the one or more media content.

16. The storage medium of claim 14, wherein the instructions, when executed, further cause determining the one or more valuations for one or more media content by weighting advertising media content higher when the advertising media content is not trending, when metadata associated with the advertising media content is similar to user generaldemographics, when the metadata associated with the advertising media content is similar to user specific demographics, when the metadata associated with the advertising media content is similar to user behaviors, when the metadata associated with the advertising media content is similar to user interests, and when the metadata associated with the advertising media content is similar to user browsing histories.

17. The storage medium of claim 16, wherein the instructions, when executed, further cause determining the one or more valuations for the one or more media content by weighting the advertising media content according to fuzzy logic based on how similar the metadata associated with the advertising media content is to user general demographics, user specific demographics, user behaviors, user interests, and user browsing histories.

18. The storage medium of claim 14, wherein the instructions, when executed, further cause determining the one or more valuations for one or more media content by weighting non-advertising media content higher when the non-advertising media content is trending, when metadata associated with the non-advertising media content is similar to user general demographics, when the metadata associated with the non-advertising media content is similar to user specific demographics, when the metadata associated with the non-advertising media content is similar to user behaviors, when the metadata associated with the nonadvertising media content is similar to user interests, and when the metadata associated with the non-advertising media content is similar to user browsing histories.

19. The storage medium of claim 18, wherein the instructions, when executed, further cause determining the one or more valuations for the one or more media content by weighting the non-advertising media content according to fuzzy logic based on how similar the metadata associated with the non-advertising media content is to the user general demographics, the user specific demographics, the user behaviors, the user interests, and the user browsing histories.

20. The storage medium of claim 14, wherein the instructions, when executed, further cause, based on outputting the second media content, adjusting the credit count in the user profile to reflect the valuation for the second media content.

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