Method, system, and computer program for a private interactive mode on a media platform

Abstract

A method for providing media content to a user in a private interactive mode on a media platform is provided. The media platform having a user interface and a recommendation engine can provide a first interactive mode and a private interactive mode. The recommendation engine can generate media content recommendations based on a user request or action. When the user exits the private interactive mode, information associated with the private interactive mode can be permanently deleted. The recommendation engine operating in the first interactive mode can be independent of information associated with the private interactive mode.

Description

[Technical Field]

[0001] [CROSS-REFERENCE TO RELATED APPLICATIONS] This application claims priority to U.S. Application No. 18 / 172,438, filed February 22, 2023, entitled "PRIVATE INTERACTIVE MODE ON MEDIA PLATFORM," the disclosure of which is incorporated herein by reference in its entirety.

[0002] FIELD OF THE INVENTION The embodiments described herein relate generally to the operation of a media platform or application that provides media content. More specifically, the embodiments described herein relate to a private interactive mode on a media platform or application that provides media content. [Background technology]

[0003] A media platform or application allows a user to create an account to browse media content (e.g., to watch videos) and provides the user with media content recommendations accordingly. If a user explores and watches a new type of video that is different from the user's primary interest, the media platform or application may begin recommending the new type of video the user just watched, even though the user may want recommendations based on the user's primary interest. For example, a user's primary interest is watching videos about plumbing and construction through a media platform or application on a smartphone. One day, the user clicks on several dance videos and watches these dance videos through the media platform or application on the smartphone. The next day, when the user opens the media platform or application on the smartphone, there are many recommendations for dance videos, but the user still wants recommendations based on their primary interest, i.e., plumbing and construction. Summary of the Invention [Problem to be solved by the invention]

[0004] A feature of embodiments disclosed herein relates to a private interactive mode on a media platform that provides media content to users. The private interactive mode described herein allows a user to explore and obtain media content within a session without affecting the user's first interactive mode associated with the user's profile on the media platform. For example, in the above example, the user could use the private interactive mode to watch dance videos on the media platform without affecting the user's first interactive mode, which provides recommendations based on their primary interests, i.e., plumbing and construction. [Means for solving the problem]

[0005] In one exemplary embodiment, a method for providing media content using a private interactive mode on a media platform is provided. The method includes providing the media platform with a user interface and a recommendation engine. The media platform is configured to provide a first interactive mode and the private interactive mode. The method further includes receiving, via the user interface, an instruction to enter the private interactive mode; generating, in the private interactive mode, via the recommendation engine, one or more media content recommendations based on one or more predetermined parameters; receiving, in the private interactive mode, via the user interface, one or more indications of a user request including user interactions corresponding to the one or more media content recommendations; generating, in the private interactive mode, via the recommendation engine, additional media content recommendations based on the received one or more indications of the user request; and, upon receiving an instruction to exit the private interactive mode, permanently deleting information associated with the private interactive mode. In some cases, the recommendation engine operating in the first interactive mode is independent of the information associated with the private interactive mode.

[0006] In another exemplary embodiment, a method for obtaining media content using a private interactive mode on a media platform is provided. The method includes: providing an instruction via a user interface of the media platform to enter the private interactive mode from a first interactive mode on the media platform; receiving, in the private interactive mode, via the user interface, one or more media content recommendations based on one or more predetermined parameters; providing, in the private interactive mode, via the user interface, one or more indications of user requests including user interactions corresponding to the one or more media content recommendations; receiving, in the private interactive mode, from the recommendation engine, additional media content recommendations based on the one or more indications of user requests; and providing an instruction to exit the private interactive mode. When the private interactive mode is exited, information associated with the private interactive mode is permanently deleted.

[0007] In yet another exemplary embodiment, a system for providing media content using a private interactive mode on a media platform is provided. The system includes: a memory configured to store data; and a processor configured to read the data from the memory and to provide a media platform having a user interface and a recommendation engine. The media platform is configured to provide a first interactive mode and the private interactive mode. The processor is further configured to: receive an instruction via the user interface to enter the private interactive mode; generate, in the private interactive mode, via the recommendation engine, one or more media content recommendations based on one or more predetermined parameters; receive, in the private interactive mode, one or more indications of a user request via the user interface, the user request including a user interaction corresponding to the one or more media content recommendations; generate, in the private interactive mode, via the recommendation engine, additional media content recommendations based on the received one or more indications of the user request; and, upon receiving an instruction to exit the private interactive mode, permanently delete data associated with the private interactive mode from the memory. [Brief explanation of the drawings]

[0008] The accompanying drawings illustrate various embodiments of the disclosed systems, methods, and various other aspects of the present disclosure. Those skilled in the art will understand that illustrated element boundaries (e.g., boxes, groups of boxes, or other shapes) in the drawings represent exemplary boundaries. In some examples, one element may be designed as multiple elements, or multiple elements may be designed as one element. In some examples, an element shown as an internal component of one element may be realized as an external component within another element, and vice versa. A non-limiting and non-exhaustive description is provided below with reference to the drawings. Components in the figures are not necessarily to scale, emphasis instead being placed on illustrating principles. Because various changes and modifications may become apparent to those skilled in the art from the following detailed description, the embodiments are described by way of illustration only. [Figure 1] FIG. 1 illustrates an example system capable of implementing a media platform that provides a private interactive mode, in accordance with at least some embodiments described herein. [Figure 2] 1 is a flowchart illustrating an example process by which a private interactive mode can be implemented on a media platform for providing media content, according to at least some embodiments described herein. [Figure 3] 1 is a flowchart illustrating an example process by which a private interactive mode can be implemented on a media platform for users to obtain media content, according to at least some embodiments described herein. [Figure 4] FIG. 1 illustrates an example information flow when utilizing a private interactive mode on a media platform, in accordance with at least some embodiments described herein. [Figure 5] FIG. 1 is a schematic block diagram of an example computer system applicable to implementing an electronic device arranged in accordance with at least some embodiments described herein. DETAILED DESCRIPTION OF THE INVENTION

[0009] In the following detailed description, specific embodiments of the present disclosure will be described with reference to the accompanying drawings, which form a part of the specification. Throughout the specification and drawings, like reference numerals represent elements capable of performing the same, similar, or equivalent functions, unless the context dictates otherwise. Furthermore, unless otherwise specified, the description of each successive drawing may refer to features of one or more previous drawings to provide a clearer context and a more substantive description of the present exemplary embodiments. However, the embodiments described in the detailed description, drawings, and claims are not intended to be limiting. Other embodiments may be utilized, and other changes may be made, without departing from the spirit or scope of the subject matter presented herein. It is understood that aspects of the present disclosure, as generally described herein and illustrated in the drawings, may be arranged, substituted, combined, separated, and designed in various different configurations, all of which are expressly contemplated herein.

[0010] It should be understood that the disclosed embodiments are merely examples of the present disclosure, which can be embodied in various forms. To avoid obscuring the present disclosure in unnecessary detail, well-known functions or structures are not described in detail. Therefore, specific structural and functional details described herein should not be construed as limitations, but merely as a basis for the claims and as a representative basis for teaching those skilled in the art to utilize the present disclosure in its various forms in substantially appropriate structural details.

[0011] Also, while the present disclosure may be described in terms of functional block components and various processing steps, it should be understood that such functional blocks may be realized by any number of hardware and / or software components configured to perform the specified functions.

[0012] The scope of the present disclosure should be determined by the appended claims and their legal equivalents, rather than by the examples given herein. For example, the steps recited in any method claim may be performed in any order and are not limited to the order recited in the claims. Also, no element is essential to the practice of the present disclosure unless specifically described herein as "critical" or "essential."

[0013] As referred to herein, a "media platform," "media application," "social media platform," or "social media application" may refer to an application on which algorithms and / or programs may be hosted that enable the execution or realization of a collection of communication-based or media-sharing technologies. Additionally, any algorithms or programs described, cited, or suggested herein may be executed by one or more processors hosted on such a platform. Non-limiting examples of such technologies may include the creation, sharing, and / or storage of multimedia offerings.

[0014] As referred to herein, "machine learning," also referred to herein as "ML," may refer to a learning or trained computer or processor-related technique that autonomously makes decisions and / or takes actions in lieu of human intervention. ML may refer to software, i.e., algorithms and / or programs, hardware or firmware, or any combination thereof, that support machine learning, natural language understanding, natural language processing, speech recognition, computer vision, etc. Model training or tuning also falls within the scope of ML functionality and capabilities and is relevant to the embodiments disclosed, referenced, and suggested herein.

[0015] As referred to herein, a "model" may refer to software, e.g., algorithms and / or programs, hardware or firmware, or any combination thereof, that supports machine learning, natural language understanding, natural language processing, speech recognition, computer vision, etc.

[0016] As described herein, an "engine" may refer to any type of software, firmware, hardware, or any combination thereof that facilitates the generation of source code or markup for generating elements that initiate another process. Additionally or alternatively, the engine or generator may facilitate an automated process in which various software elements interact to generate an envisioned product, whether physical or virtual, based on a natural language description, input, or other prompt. In accordance with known ML techniques, the ML engines or generators disclosed, referenced, and / or suggested herein are trained according to either a unimodal training model or a multimodal training model.

[0017] As used herein, a "user experience session in a mode on a media platform" may refer to the user experience during the period from when a user enters a mode on a media platform until when the user exits that mode on the media platform.

[0018] According to features of the embodiments disclosed herein, a private interactive mode is provided on a media platform to provide media content to a user in addition to a normal user mode associated with the user's profile on the media platform. The private interactive mode described herein allows a user to search for and obtain media content within a session without affecting the user's normal user mode. The private interactive mode described herein also provides a higher level of privacy and control over user data and experience when using the media platform compared to a normal user mode associated with a user profile. It should be understood that exemplary numbers are used to describe features in the embodiments described herein. However, the embodiments described herein are not limited to the described numbers. That is, the numbers described herein are provided for illustrative purposes only and are not intended to be limiting.

[0019] FIG. 1 illustrates an example system 100 in which a media platform may be implemented to provide a first interactive mode (first mode) 122 and a private interactive mode (second mode) 124, according to at least some embodiments described herein.

[0020] 1, the system 100 implements a media platform 104 including a user interface 102 at a user terminal device side and a recommendation engine 126 at a media platform provider side. The user interface 102 is connected to the recommendation engine 126 of the media platform 104 via a wireless or wired connection. The user interface 102 can provide user instructions 103 of various user requests, actions, interactions, or inputs to the media platform 104, and the recommendation engine 126 in the media platform 104 can provide media content recommendations to the user interface 102 for presentation to the user.

[0021] Upon receiving a user request via the user interface 102 to operate on the media platform in the first interactive mode 122 or the private interactive mode 124, the system 100 can implement the media platform to provide the corresponding mode, i.e., the first interactive mode 122 or the private interactive mode 124.

[0022] The interfaces 102 may include graphical user interfaces (GUIs), command lines, or any other suitable interfaces. The media platform's GUI may be displayed on one or more terminal devices at the user's site.

[0023] According to at least some embodiments, the terminal device may be any of a variety of electronic devices that have a display screen with audio and / or video input and output and that support media content, including, but not limited to, a smartphone, a tablet computer, an e-reader, an MP3 (Movie Experts Group Audio Layer III) player, an MP4 (Movie Experts Group Audio Layer IV) player, a laptop computer, a desktop computer, and / or any other suitable electronic device.

[0024] The media platform 104, including the recommendation engine 126, may be hosted by one or more of a server or cluster of servers. Users may utilize one or more terminal devices to interact with the media platform 104 over a network, for example, to request, send, or receive media content. Various applications, such as social media applications, video playback applications, etc., may be installed on the terminal devices to facilitate interaction between users and the media platform 104.

[0025] According to at least some example embodiments, a network may be a medium used to provide a communications link between one or more end devices and one or more servers or clusters of servers. The network may be the Internet, a local area network (LAN), a wide area network (WAN), a local interconnect network (LIN), the cloud, etc. The network may enable users' online activities and may be implemented with various types of connections, such as wired communications links, wireless communications links, fiber optic cables, etc.

[0026] One or more of the servers or server clusters on which the media platform 104 is hosted, and thus on which automatic data generation is realized, may refer to a high-performance computing (HPC) environment that includes at least a CPU and a GPU, e.g., present on a video card, embedded in a motherboard, or on a CPU die. Training and / or the resulting automatic data generation, i.e., dataset augmentation, may be performed entirely on the CPU or partially on the CPU and GPU. Alternative embodiments may be implemented within advanced HPC components known in the art. Nevertheless, the CPU, GPU, and / or HPC components may store one or more algorithms and / or programs that, when executed thereon, may cause the performance or execution of operations and / or functions as disclosed and / or cited herein. Also, in accordance with embodiments described herein, a computer-readable non-volatile medium may be provided. The computer-readable medium stores a computer program that, when executed by a processor, is used to perform or execute operations or functions associated with at least the embodiments described and cited herein.

[0027] The system 100 may implement a media platform to provide a first interactive mode 122, such as a normal mode, a regular mode, or a user profile mode in which a user can log in to a user account (e.g., a social network account) associated with the user's profile.

[0028] In the first interactive mode 122, the recommendation engine 126 can implement or use one or more models to generate media content recommendations tailored for the user logged into the user account. The media content recommendations may be presented to the user via the user interface 102. The models may be generated to provide personalized recommendations to the user and help the user have a more personalized experience. In some cases, the models may be obtained by considering a combination of factors including, for example, user interactions, media content information, user device and account settings, etc. Exemplary user interactions include liking or sharing media content (e.g., a video), following another user's account, posting a comment, creating or uploading media content, etc. Media content information may include details such as subtitles, sounds, hashtags, etc. User device and account settings may include, for example, user language preferences, country settings, device type, etc. The user interface 102 can receive user interactions, such as when a user plays / listens / views particular media content, posts comments about particular media content, follows other users' accounts, likes or shares particular media content, indicates disinterest in particular media content, creates or uploads particular media content, etc., through the interface 102.

[0029] In some cases, the one or more models used by the recommendation engine 126 in the first interactive mode 122 may include one or more machine learning models. For example, the machine learning models in the first interactive mode 122 may be obtained or trained using various input data, for example, related to user preferences or points of interest. For example, the various input data, including user interactions, may be processed by the recommendation engine 126 and applied to tune parameters in the machine learning models.

[0030] Information associated with the first interactive mode 122, including, for example, the user's interactions with the media platform during a session of the user's use of the media platform, may be stored by the system 100 in a user profile associated with the user account. Here, a "session using the media platform" may refer to the user's experience during the period from when the user logs into the first interactive mode 122 until when the user logs out. The user's profile may include any data associated with the user's use of the media platform in the first interactive mode 122. In the first interactive mode 122, the media platform may update the user's profile and use the data in the user's profile to generate media content recommendations for the user via the recommendation engine 126. For example, when the user interface 102 receives an instruction from the user to enter the user interactive mode 122 (e.g., the user logs into the media platform), the media platform may generate and present various information associated with the user profile via the user interface 102. The user interface 102 may further present recommended media content in various categories, including, for example, new releases, recently viewed media content, the user's media library, etc.

[0031] The system 100 may further implement the media platform 104 to provide a private interactive mode 124. In the first interactive mode 122 (e.g., normal mode), the user interface 102 may receive a user request to enter the private interactive mode 124. Upon receiving the user's request, the system 100 allows the user to enter the private interactive mode 124 from the normal mode, and the user interface 102 may indicate to the user on the media platform 104 that the user is in the private interactive mode 124. For example, when a user logs into a user account associated with a user profile on a terminal device (e.g., a smartphone) through the media platform's user interface 102, the user interface 102 may provide a selectable profile icon, and the user can tap the selectable profile icon to exit the first interactive mode 122 (e.g., normal mode) and enter the private interactive mode 124. When the user enters the private interactive mode 124, the user interface 102 may present a message confirming that the private interactive mode 124 is on. The user interface 102 may further provide a selectable icon in the private interactive mode 124 that the user can select to tap to exit the private interactive mode 124. The user interface 102 may receive a user indication to enter and exit the private interactive mode 124 by any suitable user action, such as touch, voice, eye movement, etc.

[0032] When the user interface 102 receives a user request to exit the first interactive mode 122 and enter the private interactive mode 124, the system 100 stops providing any received user action or request indications 103 to the one or more models used by the recommendation engine 126 associated with the first interactive mode 122. The system 100 may generate one or more new models for the recommendation engine 126 associated with the private interactive mode 124. While operating in the private interactive mode 124, any received user action or request indications 103 may be provided to the new models implemented by the recommendation engine 126 to generate recommendations.

[0033] In some cases, the new model may be generated by modifying one or more of the models used by the recommendation engine 126 associated with the first interactive mode 122. For example, these models may include a multi-layer neural network structure with parameters as connection weights. The modified model may add, remove, or modify one or more of the layers in the multi-layer neural network structure and / or change one or more parameters of the neural network. It should be understood that the modified model associated with the private interactive mode 124 may be independent of the model associated with the first interactive mode 122 and does not use user data (e.g., the user's browsing history, preferences, etc.) associated with the user profile in the first interactive mode 122.

[0034] According to non-limiting embodiments described and cited herein, the new model associated with the private interactive mode 124 may be used by the recommendation engine 126 during a session of operating the private interactive mode 124, for example, from the time the user enters the private interactive mode 124 until the user exits the private interactive mode 124. In other words, the recommendation engine 126 may use the new model associated with the private interactive mode 124 to learn the user's interests or preferences and provide media content recommendations during a single session of the user's experience in the private interactive mode. This may be different from the first interactive mode 122 (e.g., normal mode), in which a user model may be associated with a user profile. The recommendation engine 126 may use the user model to learn the user's interests or preferences and provide media content recommendations during each session of the user's experience in the normal mode, as long as the user is logged into their user account.

[0035] In some cases, the new model associated with the private interactive mode 124 may be generated with parameters or rules to learn the user's interests or preferences at a relatively faster rate than the model associated with the user profile in the first interactive mode 122 (e.g., normal mode). For example, the model associated with the private interactive mode 124 may be generated with appropriate parameters or rules to provide relatively more media content recommendations within a given period of time compared to the first interactive mode 122 (e.g., normal mode).

[0036] In some cases, depending on the length of the session (e.g., from a few minutes to a few hours), a new model associated with the private interactive mode 124 may be generated with different parameters or rules to learn the user's interests or preferences at different rates. For example, if the session length is relatively short, a model may be generated with appropriate parameters or rules to provide more media content recommendations within a given period of time.

[0037] In some cases, the recommendation engine 126 may use the new model associated with the private interactive mode 124 to generate recommendations for short videos having a maximum length. For example, the length of the short videos may be up to 5 minutes, up to 3 minutes, up to 2 minutes, up to 1 minute, up to 30 seconds, up to 20 seconds, or even up to 10 seconds. The length of the short videos may be at least 1 second, at least 2 seconds, or at least 3 seconds. In some cases, the recommendations for short videos may include a combination of multiple short videos having different lengths.

[0038] When a user enters the private interactive mode 124, the recommendation engine 126 can generate one or more media content recommendations based on one or more predetermined parameters. The one or more predetermined parameters may include, for example, device information (e.g., device type, screen size, etc.), language settings, geographic information such as location or country settings, locale information, etc. These parameters may be predetermined, for example, by extracting relevant device information from a terminal device (e.g., a smartphone) used by the user to communicate with the media platform.

[0039] In some cases, the recommendation engine 126 may use one or more predetermined parameters based on local cookie information stored on the user's terminal device (e.g., a smartphone). It should be understood that the recommendation engine 126 may not use cookie information stored on the media platform provider's (e.g., server) side. It should also be understood that in one embodiment, cookie information associated with the normal mode may not be used. Also, the local cookie information stored on the user's terminal device may not be updated to reflect the use of the private interactive mode 124 on the user's media platform.

[0040] In some cases, the recommendation engine 126 may use one or more predetermined parameters to tailor general recommendations provided to new users of the media platform. General recommendations for new users may include, for example, trending content that is currently popular and receiving a relatively high level of engagement from users of the media platform, emerging content that is beginning to gain traction on the media platform and continues to grow in audience, and live content currently being broadcast in real time on the media platform. The tailored recommendations generated by the recommendation engine 126 for users utilizing the private interactive mode 124 may be user-specific or device-specific, for example, by taking into account one or more predetermined parameters (e.g., location, language, device type, screen size, locale, local cookie information, etc.). These parameters may be predetermined by extracting them from the terminal device (e.g., smartphone) currently being used by the user to communicate with the media platform.

[0041] In some cases, one or more predetermined parameters can be provided as input data for a model used by the recommendation engine to generate media content recommendations in private interactive mode 124. For example, language information and / or location information from the user's device may be used to tune the model to generate appropriate recommendations in private interactive mode 124.

[0042] In some cases, the media platform may generate a user-interest list of selectable categories, e.g., via the recommendation engine 126, and present it to the user, e.g., via the user interface 102. The user may select one or more items from the list to indicate their interests or preferences. In some cases, the list of selectable categories may be generated taking into account one or more predetermined parameters, e.g., the user's preferred language. The generated list of selectable categories may be tailored for different users according to one or more predetermined parameters. For example, in one embodiment, different lists may be generated for users who use different languages. In one embodiment, different lists may be generated if at least one of the predetermined parameters (e.g., location, device type, screen size, locale, local cookie information, etc.) is different.

[0043] It should be understood that a user may provide input or requests in any suitable manner via the user interface. In some cases, a user may indicate a user interest or preference by filling out a form, requesting one or more selections, selecting one or more items from a list in a form, searching for media content via a search tool (e.g., a search bar, search box, search field), interacting with presented media content (e.g., expressing a "like" or "dislike" for presented media content), combinations thereof, etc. For example, in a private interactive mode, a user may indicate a user interest in "dance videos" via the user interface 102 by filling out a form, submitting a search request, selecting from a predetermined list, clicking a "like" feature for presented dance videos, clicking a play button for presented dance videos, etc. It should be understood that when a user exits private mode, the user's actions or interactions with the media content may be permanently deleted, as described further below.

[0044] Upon receiving user input via the user interface 102, the recommendation engine 126 may generate media content recommendations based on the user input in addition to predetermined parameters. In some cases, the user input or instructions can be provided as input data for a model used by the recommendation engine to generate the media content recommendations.

[0045] When a user receives recommended media content via the user interface 102, the user may perform one or more user actions via the user interface 102. For example, the user may play, select, view, like, or dislike the received media content. An indication of the one or more user actions may be received by the user interface 102 and provided to the recommendation engine 126 as user feedback data. For example, the user interface 102 may track the amount of time the user views the received media content and provide the time data to the recommendation engine 126 as user feedback data. It should be understood that the user feedback data is not limited to user actions or requests corresponding to the received media content recommendation. For example, the user action may be a request to play certain media content (e.g., a short video) that may or may not be within the received recommendation, in which case the media platform 104 may provide the requested short video to the user interface 102 for playback.

[0046] In some cases, the user interface 102 in the private interactive mode 124 may not allow the user to enter comments on the received media content. To leave a comment via the user interface 102, the user may need to exit the private interactive mode 124. Upon receiving a user instruction to exit the private interactive mode 124, the user interface 102 may allow the user to exit the private interactive mode 124 and re-enter the first interactive mode (normal mode) 122 in which the user can enter comments about the media content. Comments on media content received in the normal mode associated with the user's profile may not be provided to the recommendation engine 126 as user feedback data associated with the private interactive mode 124. If the user exits the private interactive mode 124, the system 100 may allow the user to automatically return to the normal mode 122 according to default settings (e.g., provided by a mobile or web application). In some cases, the user may need to log in to a user account to use the normal mode. In some cases, the user may have the option to log in or remain logged out to use the normal mode. In some cases, a user may be required to log into a user account in order to enter comments on the media content.

[0047] In some cases, user feedback data associated with the private interactive mode 124 can be provided as input data to a model implemented by the recommendation engine 126 associated with the private interactive mode 124 to tune or train the model. The tuned or trained model can be used to generate additional media content recommendations, which may require additional user feedback data to further tune or train the model associated with the private interactive mode 124. By repeatedly providing recommendations and receiving feedback data from the user, the recommendation engine 126 can tune the model to recommend media content that reflects the user's preferences or interests when using the media platform in the private interactive mode 124. In other words, the recommendation engine 126 may use the model associated with the private interactive mode 124 during a session in which the private interactive mode 124 is operated. Here, a "session" may refer to the period from when a user enters the private interactive mode 124 to when the user exits the private interactive mode 124.

[0048] When the user interface 102 receives an instruction from the user to exit the private interactive mode 124, the system 100 may permanently delete from the system 100 all data or information associated with the private interactive mode 124. Generally, user data associated with a session of use of the media platform by a user in the private interactive mode 124 may be deleted when the user exits that usage session. In some cases, when receiving an instruction to exit the private interactive mode 124, the system 100 may permanently delete all data or information that was used as input data to tune or train models used by the recommendation engine 126 in the session operating the private interactive mode 124. The system 100 may permanently delete all data or information that was output data of models used by the recommendation engine 126 in that session.

[0049] The data or information deleted upon exiting private interactive mode 124 may further include, for example, user input indicating the user's interests or preferences during a session operating private interactive mode 124, past media content recommendations provided to the user, user actions serving as feedback data for the recommendations, user browsing information, user viewing and interaction history, cookie information, form data, etc. For example, if a user exits a session utilizing private interactive mode after watching dance videos on the user's smartphone, the user data within that session, including past recommendations for dance videos, the user's browsing history of dance videos, the user's viewing and interaction history of dance videos, etc., may be permanently deleted when private interactive mode is exited.

[0050] The term "permanently delete" may refer to the data or information being deleted not having a backup or being recovered / restored in the system 100 or any physical device (e.g., memory) upon exiting the private interactive mode 124. The system 100 may also not allow the data or information associated with the private interactive mode 124 to be linked to the user's profile prior to deletion of the data or information.

[0051] In some cases, media platform 104 may track user actions or interactions with particular media content without associating the actions or interactions with any user or user profile. In other words, media platform 104 may use data about user actions associated with media content without receiving and storing personal user information associated with a user profile. For example, media platform 104 may track the number of views or likes received for particular media content (e.g., a dance video) without associating the actions with the user who performed the actions.

[0052] In some cases, the recommendation engine 126 operating in the first interactive mode 122 may be independent of information associated with the private interactive mode 124. For example, user instructions 103 received by the user interface 102 in the private interactive mode 124 may not be provided to the recommendation engine 126 in the first interactive mode 122. Input and output data of the recommendation engine 126 operating in the private interactive mode 124 may not be provided to the recommendation engine 126 operating in the first interactive mode 122.

[0053] In some cases, the recommendation engine 126 operating in the private interactive mode 124 may be independent of information associated with the first interactive mode 122. For example, user instructions 103 received by the user interface 102 in the first interactive mode 122 may not be provided to the recommendation engine 126 operating in the private interactive mode 124. Input and output data of the recommendation engine 126 operating in the first interactive mode 122 may not be provided to the recommendation engine 126 operating in the private interactive mode 124.

[0054] 2 is a flowchart illustrating an example process 200 by which a private interactive mode can be implemented on a media platform to provide media content, according to at least some embodiments described herein. Processing flow 200 may include various operations, functions, or actions, as indicated by one or more of blocks 210, 220, 230, 240, and 250. These various operations, functions, or actions may correspond to, for example, software, program code, or program instructions executable by a processor to cause those functions to be performed. Processing may begin at block 210.

[0055] At block 210, a media platform having a user interface and a recommendation engine and providing a first interactive mode and a private interactive mode is provided. For example, as shown in the embodiment of FIG. 1, the media platform may be implemented by system 100 to have user interface 102 and recommendation engine 126 and provide first interactive mode 122 and private interactive mode 124. Processing 200 then proceeds to block 220.

[0056] At block 220, the recommendation engine 126 generates one or more media content recommendations in the private interactive mode 124 based on one or more predetermined parameters. The one or more predetermined parameters may include, for example, device type, language setting, location or country setting, etc. In some cases, the user interface 102 may receive user input indicating user interests or preferences, and the recommendation engine can generate media content recommendations based on the user input in addition to the predetermined parameters. In some cases, the one or more predetermined parameters and the user input or instructions can be provided as input data for one or more models used by the recommendation engine to generate media content recommendations in the private interactive mode. The process 200 then proceeds to block 230.

[0057] At block 230, the user interface 102 receives, in the private interactive mode, one or more indications of a user request, including a user action based on the received one or more media content recommendations. The user action may include, for example, playing, selecting, viewing, liking, or disliking the received media content. It should be understood that the user action or request may further include any user input to indicate the user's interest or preference regarding the provided media content. The one or more indications of the user action or request may be provided to the recommendation engine 126 as user feedback data. The processing 200 then proceeds to block 240.

[0058] At block 240, the recommendation engine 126 generates additional media content recommendations based on one or more indications of user requests or actions received in the private interactive mode, including user feedback data. In some cases, the user feedback data associated with the private interactive mode can be provided as input data to tune or train one or more models used by the recommendation engine 126 associated with the private interactive mode. The tuned or trained models can be used to generate additional media content recommendations, which may require additional user feedback data to further tune or train models in the same session of using the media platform in the private interactive mode. Processing 200 then proceeds to block 250.

[0059] In block 250, if the user interface 102 receives an instruction to exit the private interactive mode, the system 100 may permanently delete information associated with the private interactive mode. Generally, any user data associated with a session of use of the media platform by a user in the private interactive mode 124 may be deleted when the user exits that usage session. For example, the recommendation engine 126 may permanently delete input or output data associated with models for that session. The system 100 may also delete, for example, user inputs indicating the user's interests or preferences, past media content recommendations provided to the user, user actions serving as feedback data for recommendations, user browsing information, the user's viewing and interaction history, cookie information, form data, etc., used or captured in a session in which the user operates the private interactive mode.

[0060] 3 is a flowchart illustrating an example process 300 by which a private interactive mode can be implemented on a media platform for a user to obtain media content, according to at least some embodiments described herein. Processing flow 300 may include various operations, functions, or actions, as indicated by one or more of blocks 310, 320, 330, 340, and 350. These various operations, functions, or actions may correspond to, for example, software, program code, or program instructions executable by a processor to cause those functions to be performed. Processing may begin at block 310.

[0061] At block 310, a user may provide an instruction via the media platform's user interface 102 to enter the private interactive mode 124 from the first interactive mode 122 on the media platform 104. For example, the user may tap an icon within the user interface 102 to select to exit the normal mode associated with the user profile and enter the private interactive mode. Processing 300 then proceeds to block 320.

[0062] At block 320, the user may receive, in a private interactive mode, one or more media content recommendations from the recommendation engine 126 via the user interface 102 based on one or more predetermined parameters. The predetermined parameters may include, for example, device type, language setting, geographic information such as location or country setting, and the like. In some cases, the user may provide input to indicate interests or preferences in response to a query posed by the user interface 102, and the recommendations may be based on the indicated user interests or preferences. In some cases, the recommendations may include a general feed of popular media content (e.g., videos). Processing 300 then proceeds to block 330.

[0063] At block 330, the user may provide, in the private interactive mode, via the user interface 102, one or more indications of a user request including user interactions corresponding to one or more media content recommendations. The user indications may serve as feedback data that enables a model implemented by the recommendation engine 126 to learn the user's interests or preferences during the private interactive mode operating session. Processing 300 then proceeds to block 340.

[0064] At block 340, the user, in the private interactive mode, receives, via the user interface 102, recommendations for additional media content generated by the recommendation engine 126 based on one or more indications of the user request. By repeatedly receiving recommendations from and providing feedback to the recommendation engine, the user can help tune the model to recommend media content that reflects the user's preferences during a session of using the media platform in the private interactive mode. Processing 300 then proceeds to block 350.

[0065] In block 350, the user provides an indication to exit the private interactive mode via the user interface 102. For example, the user may tap a selectable icon on the user interface 102 while in the private interactive mode to select to exit the private interactive mode. When the user exits, the system 100 may permanently delete data and information associated with the user's session of using the media platform in the private interactive mode. Because the data and information is deleted, when the user enters normal mode or a new session in the private interactive mode, the user's experience may not be affected by the user's activity in the previous session in the private interactive mode.

[0066] FIG. 4 illustrates an exemplary information flow for operating a private interactive mode on a media platform that provides media content to a user, according to at least some embodiments described herein. As shown in FIG. 4 , at 401, the media platform may provide a first interactive mode, e.g., a normal mode, to allow a user to log in to a user account. At 402, using the normal mode on the media platform may include receiving, via a user interface, media content associated with a user profile provided by the media platform provider. At 403, the user interface may receive a user instruction to enter the private interactive mode from the normal mode. At 404, while operating in the private interactive mode, a recommendation engine may generate media content recommendations based on predetermined parameters. At 405, a user may receive the recommendation via the user interface. Upon receiving a media content recommendation from the recommendation engine at 407, the user may input feedback corresponding to the received recommendation or a user request or instruction for action. At 408, the feedback data may be provided to the recommendation engine. At 409, the received user feedback causes the recommendation engine to generate additional media content recommendations that may be provided to the user interface at 410, and may solicit additional user feedback to further tune or train the model of the recommendation engine associated with the private interactive mode. By iteratively providing recommendations and receiving feedback data from the user, the recommendation engine at the media content provider can tune its model to recommend media content that reflects the user's preferences or interests.If the user indicates at 411 to exit the private interactive mode, the user data and information associated with the session operating the media platform in the private interactive mode may be permanently deleted at 412. With the user data and information associated with the session deleted, when the user re-enters normal mode at 401 and / or starts a new session in the private interactive mode at 403, the user experience may not be affected by the user's previous sessions operating the media platform in the private interactive mode.

[0067] 5 is a schematic block diagram of an exemplary computer system 500 in which the process and any of the subprocesses for operating a private interactive mode on a media platform to provide media content may be implemented as executable instructions stored on a non-volatile computer-readable medium. The computer-readable instructions may be executed, for example, by a processor of a device comprising a network element and / or any other device corresponding thereto as referenced herein, and are particularly applicable to the applications and / or programs described above corresponding to system 100 for implementing a media platform. It should be understood that the computer system illustrated in FIG. 5 is provided for illustrative purposes only, and does not limit the functionality and application of the embodiments described herein.

[0068] As shown, computer system 500 may include a central processing unit (CPU) 505. CPU 505 may perform various operations and processes based on programs stored in read-only memory (ROM) 510 or programs loaded from storage device 540 into random access memory (RAM) 515. RAM 515 may also store various data and programs required for the operation of system 500. CPU 505, ROM 510, and RAM 515 may be connected to each other via bus 520. Input / output (I / O) interface 525 may also be connected to bus 520.

[0069] Components connected to the I / O interface 525 may further include an input device 530 including a keyboard, mouse, digital pen, drawing pad, etc.; an output device 535 including a display such as an LCD display, a speaker, etc.; a storage device 540 including a hard disk, etc.; and a communication device 545 including a network interface card such as a LAN card, a modem, etc. The communication device 545 may perform communication processing via a network, such as the Internet, a WAN, a LAN, a LIN, the cloud, etc. In an exemplary embodiment, a driver 550 may also be connected to the I / O interface 525. A removable medium 555 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. may be mounted in the driver 550 as needed so that a computer program read from the removable medium 555 may be installed in the storage device 640.

[0070] It should be understood that the processes described with reference to the flowcharts of Figures 2-4 and / or the processes described in other figures may be implemented as a computer software program or in hardware. A computer program product may include a computer program stored on a computer-readable non-volatile medium. The computer program includes program code for executing the methods shown in the flowcharts and / or GUIs. In this embodiment, the computer program may be downloaded and installed from a network via the communication device 545 or from a removable medium 555. When executed by the central processing unit (CPU) 505, the computer program can implement the functions defined in the methods in the embodiments disclosed herein.

[0071] It should be understood that the disclosed and other solutions, examples, embodiments, modules, and functional operations described herein may be implemented in digital electronic circuitry, or in computer software, firmware, or hardware, including the structures disclosed herein and their structural equivalents, or in any combination of one or more of these. The disclosed and other embodiments may be implemented as one or more computer program products, i.e., one or more modules of computer program instructions encoded on a computer-readable medium, for execution by or control of the operation of a data processing device. The computer-readable medium may be a machine-readable storage device, a machine-readable storage substrate, a memory device, a composition of matter affecting a machine-readable propagated signal, or any combination of one or more of these. A "data processing device" includes all devices, apparatuses, and machines for processing data, including, for example, a programmable processor, a computer, or multiple processors or computers. An apparatus may include, in addition to hardware, code that creates the execution environment for the computer programs being discussed, such as code constituting processor firmware, a protocol stack, a database management system, an operating system, or any combination of one or more of these.

[0072] A computer program (also referred to as a program, software, software application, script, or code) may be written in any type of programming language, including compiled or interpreted languages, and may be deployed in any form, such as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment. A computer program does not necessarily correspond to a file in a file system. A program may be stored within a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program, or in multiple associated files (e.g., files storing one or more modules, subprograms, or portions of code). A computer program may be deployed to be executed on one computer, or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communications network.

[0073] The processes and logic flows described herein may be executed by one or more programmable processors executing one or more computer programs to perform functions by manipulating input data and generating output. The processes and logic flows may also be executed by, and may be implemented as, special purpose logic circuitry, such as field programmable gate arrays, application specific integrated circuits, etc.

[0074] Processors suitable for executing a computer program include, by way of example, both general-purpose and special-purpose microprocessors, and any one or more processors of any kind of digital computer. Typically, a processor receives instructions and data from a read-only memory or a random-access memory, or both. The essential elements of a computer are a processor for executing instructions and one or more memory devices for storing instructions and data. Typically, a computer also includes, or is operatively coupled to, one or more mass storage devices for storing data, such as magnetic, magneto-optical, or optical disks. However, a computer need not have such devices. Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media, and memory devices, including, for example, semiconductor memory devices such as erasable programmable read-only memory, electrically erasable programmable read-only memory, and flash memory devices; magnetic disks such as internal hard disks or removable disks; magneto-optical disks; and compact disk read-only memory and digital video disk read-only memory disks. The processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry.

[0075] It should be understood that different features, variations, and multiple different embodiments have been shown and described in various details. In this application, descriptions, sometimes with respect to specific embodiments, are done so for illustrative purposes only and are not intended to limit or suggest that only one particular embodiment or particular embodiment has been contemplated. It should be understood that the present disclosure is not limited to any single particular embodiment or variation listed. Numerous modifications, variations, and other embodiments will occur to those skilled in the art, and are intended and indeed covered by the present disclosure. It is indeed intended that the scope of the present disclosure should be determined by proper legal interpretation and construction of the disclosure, including equivalents, as understood by those skilled in the art reliant on the full disclosure as it exists at the time of filing.

[0076] Aspects:

[0077] It will be understood that any one of the aspects may be combined.

[0078] Aspect 1. A method for providing media content using a private interactive mode on a media platform, the method comprising: providing the media platform having a user interface and a recommendation engine, the media platform configured to provide a first interactive mode and the private interactive mode; receiving, via the user interface, an instruction to enter the private interactive mode; generating, in the private interactive mode, via the recommendation engine, one or more media content recommendations based on one or more predetermined parameters; receiving, in the private interactive mode, via the user interface, one or more indications of a user request including a user interaction corresponding to the one or more media content recommendations; generating, in the private interactive mode, via the recommendation engine, recommendations for additional media content based on one or more indications of the received user request; and permanently deleting information associated with the private interactive mode if an instruction to exit the private interactive mode is received.

[0079] Aspect 2: The method of aspect 1, wherein the one or more predetermined parameters include one or more of a device type, a language setting, and a location setting.

[0080]

[0013] Aspect 3: The method of aspects 1 or 2, further comprising: presenting a list of user interests for selectable categories via the user interface.

[0081]

[0013] Aspect 4. The method of aspect 3, further comprising receiving, via the user interface, an indication of a user selection of one or more of the selectable categories of user interest.

[0082]

[0013] Aspect 5: The method of aspect 4, wherein generating the one or more recommendations is further based on a received indication of a user selection.

[0083] Aspect 6: The method of any one of aspects 1 to 5, further comprising: upon receiving an instruction to enter the private interactive mode, ceasing to provide one or more instructions of the received user request to a machine learning model associated with the first interactive mode.

[0084]

[0013] Aspect 7: The method of aspect 6, further comprising: modifying the machine learning model to operate in the private interactive mode.

[0085]

[0023] Embodiment 8: The method of embodiment 7, further comprising providing one or more indications of the user request as input data to a modified machine learning model.

[0086]

[0023] Aspect 9. The method of aspect 7 or 8, further comprising: upon receiving an instruction to exit the private interactive mode, permanently deleting data associated with the modified machine learning model.

[0087] Aspect 10: The method of any one of aspects 1 to 9, further comprising: in the private interactive mode, presenting a notification of the private interactive mode via the user interface.

[0088] Aspect 11: The method of any one of claims 1 to 10, wherein the recommendation engine operating in the first interactive mode is independent of information associated with the private interactive mode.

[0089] Aspect 12. A method of obtaining media content using a private interactive mode on a media platform, the method comprising: providing an instruction via a user interface of the media platform to enter the private interactive mode from a first interactive mode on the media platform; receiving, via the user interface in the private interactive mode, one or more media content recommendations based on one or more predetermined parameters; providing, in the private interactive mode, via the user interface, one or more indications of a user request including a user interaction corresponding to the one or more media content recommendations; receiving, in the private interactive mode, via the user interface, recommendations for additional media content based on one or more indications of the user request; and providing an instruction to exit the private interactive mode, wherein when the private interactive mode is exited, information associated with the private interactive mode is permanently deleted.

[0090]

[0022] Aspect 13: The method of aspect 12, further comprising receiving, in the private interactive mode, via the user interface, a list of user interests for the selectable categories.

[0091]

[0023] Aspect 14. The method of aspect 13, further comprising: in the private interactive mode, providing, via the user interface, an indication of a user selection of one or more of the selectable categories of user interest.

[0092]

[0023] Aspect 15: The method of aspect 14, wherein the one or more recommendations are further based on the received indication of a user selection.

[0093] Aspect 16: The method of any one of aspects 12 to 15, further comprising, in the private interactive mode, receiving a notification of the private interactive mode via the user interface.

[0094] Aspect 17. A system for providing media content using a private interactive mode on a media platform, the system comprising: a memory configured to store data; and a processor configured to read the data from the memory; The processor: providing the media platform having a user interface and a recommendation engine, the media platform configured to provide a first interactive mode and a private interactive mode; receiving, via the user interface, an instruction to enter the private interactive mode; generating, in the private interactive mode, via the recommendation engine, one or more media content recommendations based on one or more predetermined parameters; receiving, in the private interactive mode, one or more indications of a user request via the user interface, the user interaction corresponding to the one or more media content recommendations; generating, in the private interactive mode, via the recommendation engine, recommendations for additional media content based on one or more indications of the received user request; When an instruction to exit the private interactive mode is received, data associated with the private interactive mode is configured to be permanently deleted from the memory.

[0095]

[0023] Aspect 18: The system of aspect 17, wherein the processor is further configured to modify a machine learning model associated with the first interactive mode to operate in the private interactive mode.

[0096]

[0023] Aspect 19: The system of aspect 18, wherein the processor is further configured to provide one or more indications of the user request as input data to a modified machine learning model.

[0097]

[0023] Aspect 20. The system of aspect 18 or 19, wherein the processor is further configured to permanently delete data associated with the modified machine learning model from the memory if the processor receives an instruction to exit the private interactive mode.

[0098] The terms used herein are intended to describe particular embodiments and are not intended to be limiting. The terms "a," "an," and "the" include the plural unless expressly indicated otherwise. The terms "comprises" and / or "comprises," when used herein, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, and / or components.

[0099] With respect to the foregoing description, it should be understood that changes may be made in details, particularly in matters of the materials of construction employed, and the shape, size and arrangement of parts, without departing from the scope of the present disclosure. The specification and described embodiments are exemplary only, with the true scope and spirit of the present disclosure being indicated by the following claims.

Claims

1. 1. A method for providing media content using a private interactive mode on a media platform, comprising: providing the media platform having a user interface and a recommendation engine, the media platform configured to provide a first interactive mode and the private interactive mode; receiving, via the user interface, an instruction to enter the private interactive mode; generating, in the private interactive mode, via the recommendation engine, one or more media content recommendations based on one or more predetermined parameters; receiving, in the private interactive mode, via the user interface, one or more indications of a user request including a user interaction corresponding to the one or more media content recommendations; generating, in the private interactive mode, via the recommendation engine, recommendations for additional media content based on one or more indications of the received user request; permanently deleting information associated with the private interactive mode upon receiving an instruction to exit the private interactive mode; and A method comprising:

2. the one or more predetermined parameters include one or more of a device type, a language setting, and a location setting; The method of claim 1.

3. presenting a list of selectable categories of user interests via said user interface; The method of claim 1 further comprising:

4. receiving, via the user interface, an indication of a user selection of one or more of the selectable categories of user interests; The method of claim 3 further comprising:

5. generating the one or more recommendations further based on the received indication of the user selection; The method of claim 4.

6. upon receiving an instruction to enter the private interactive mode, ceasing to provide the received instruction or instructions of the user request to a machine learning model associated with the first interactive mode; The method of claim 1 further comprising:

7. modifying the machine learning model to operate in the private interactive mode; The method of claim 6 further comprising:

8. providing one or more instructions of the user request as input data to a modified machine learning model; The method of claim 7 further comprising:

9. permanently deleting data associated with the modified machine learning model upon receiving an instruction to exit the private interactive mode; The method of claim 7 further comprising:

10. while in the private interactive mode, presenting a notification of the private interactive mode via the user interface; The method of claim 1 further comprising:

11. The recommendation engine operating in the first interactive mode is independent of information associated with the private interactive mode. The method of claim 1.

12. 1. A method for obtaining media content using a private interactive mode on a media platform, comprising: providing an instruction via a user interface of the media platform to enter a private interactive mode from a first interactive mode on the media platform; receiving, in the private interactive mode, via the user interface, one or more media content recommendations based on one or more predetermined parameters; providing, in the private interactive mode, via the user interface, one or more indications of a user request including a user interaction corresponding to the one or more media content recommendations; receiving, in the private interactive mode, via the user interface, recommendations for additional media content based on one or more indications of the user request; providing instructions to exit the private interactive mode; When the private interactive mode is exited, information associated with the private interactive mode is permanently deleted. method.

13. receiving, in the private interactive mode, via the user interface, a list of user interests for selectable categories; The method of claim 12 further comprising:

14. providing, in the private interactive mode, via the user interface, an indication of a user selection of one or more of the selectable categories of user interests; The method of claim 13 further comprising:

15. The one or more recommendations are further based on the received indication of user selection.

15. The method of claim 14.

16. while in the private interactive mode, receiving, via the user interface, a notification of the private interactive mode; The method of claim 12 further comprising:

17. 1. A system for providing media content using a private interactive mode on a media platform, comprising: a memory configured to store data; and a processor configured to read the data from the memory; The processor: providing the media platform having a user interface and a recommendation engine, the media platform configured to provide a first interactive mode and the private interactive mode; receiving, via the user interface, an instruction to enter the private interactive mode; generating, in the private interactive mode, via the recommendation engine, one or more media content recommendations based on one or more predetermined parameters; receiving, in the private interactive mode, one or more indications of a user request via the user interface, the user request including a user interaction corresponding to the one or more media content recommendations; generating, in the private interactive mode, via the recommendation engine, recommendations for additional media content based on one or more indications of the received user request; configured to permanently delete data associated with the private interactive mode from the memory upon receiving an instruction to exit the private interactive mode. system.

18. the processor is further configured to modify a machine learning model associated with the first interactive mode to operate in the private interactive mode.

20. The system of claim 17.

19. The processor is further configured to provide one or more indications of the user request as input data to a modified machine learning model.

20. The system of claim 18.

20. The processor is further configured to permanently delete data associated with the modified machine learning model from the memory upon receiving an instruction to exit the private interactive mode.

20. The system of claim 18.

Images