Abstract: Disclosed are systems and methods for initiating communication between users of a user group based on machine learning techniques. The disclosed systems and methods provide a novel framework for automating communication scheduling and communication initiation based on user communication objectives and machine learning techniques. The disclosed framework operates by leveraging available user provided communication parameters, user provided objectives, and various real-time data associated with the users, and using the aforementioned data as inputs for machine learning models, in order to schedule communication between the users, automatically initiate communication between the users, or transmit communication notifications to the users.

Abstract: The present teaching relates to communication related to predictions. A communication chain is created with multiple chain units, each operating independently to provide prediction services related to a prompt with embedded information therein associated with predictions for the prompt to enable prediction services. A request is received for a requested operation related to a query prompt on one of prediction solicitation, prediction entry, verification entry, and prediction access. If a chain unit for the query prompt, the request is directed to the chain unit to perform the requested operation. If not, a new chain unit is created for the query prompt and the request is forwarded to the new chain unit to carry out the requested operation.

Abstract: One or more computing devices, systems, and/or methods for content item selection for goal achievement are provided herein. A goal of a user is identified. A model is utilized to evaluate the goal, user information, and a set of content items to generate predictions for the content items of how likely each content item will be a causation factor of the user making progress towards the goal in response to the user being provided with each content item. A target content item is selected from the set of content items based upon the target content item having a predicted likelihood of being the causation factor above a threshold. The target content item is provided through a registered media channel accessible through a device of the user.

Abstract: In some aspects, the techniques described herein relate to a method including obtaining purchase history data for a plurality of users within a group, the purchase history corresponding to at least one product; determining a first product availability corresponding to the at least one product based on the purchase history data; transmitting, to a User Equipment (UE) of a user of the plurality of users, a notification including the first product availability; obtaining updated purchase history data, the updated purchase history data corresponding to the at least one product; determining a second product availability corresponding to the at least one product based on the updated purchase history data; determining a product availability change based on the first product availability and the second product availability; and modifying user rights of the user based on the product availability change.

Abstract: Methods are disclosed that include receiving electronic content data associated with an electronic content provider comprising: a content campaign identification associated with a virtual token, and provider-identified platform identifications that identify platforms on which the content campaign may be initiated; receiving input from the user comprising: a user identification, a virtual token identification, a campaign identification that identifies the content campaign associated with the virtual token, and user-identified platform identifications that identify the platforms on which the user consents to be targeted by the content campaign; determining, based on the received electronic content data and user data, the content campaign and platforms the user consents to; and generating a notification to initiate a content campaign targeting the user on the platforms on which the user consents to be targeted; and outputting the generated notification to the platforms on which the user consents to be targeted.

Abstract: In an example, a starting argument post may be received, via a first debate interface, from a first client device associated with a first user account of a debate system. A first response post may be received, via a second debate interface, from a second client device associated with a second user account of the debate system. The first response post corresponds to a response to the starting argument post. The starting argument post and the first response post are included in a first debate thread. When a first submission status of the first user account is active, submission of a response post for inclusion in the first debate thread may be enabled via the first debate interface. A second response post may be received, via the first debate interface and when the first submission status of the first user account is active, from the first client device.

Abstract: A user device may invoke, for a user associated with an unavailable user device, a guest mode, and may connect the user device with a network device based on invoking the guest mode. The user device may provide credentials of the user and a secure input of the user to the network device based on invoking the guest mode, and may receive an identity service and an emergency service for the user when the secure input is authenticated by the network device. The user device may associate, via the identity service, the user with the user device to enable the user to utilize the emergency service, and may provide, via the emergency service, one or more emergency notifications. The user device may receive an indication of the user exiting the guest mode, and may remove the credentials of the user from a memory based on the indication.

Abstract: Methods are disclosed that include receiving electronic content data associated with an electronic content provider comprising: a content campaign identification associated with a virtual token, and provider-identified platform identifications that identify platforms on which the content campaign may be initiated; receiving input from the user comprising: a user identification, a virtual token identification, a campaign identification that identifies the content campaign associated with the virtual token, and user-identified platform identifications that identify the platforms on which the user consents to be targeted by the content campaign; determining, based on the received electronic content data and user data, the content campaign and platforms the user consents to; and generating a notification to initiate a content campaign targeting the user on the platforms on which the user consents to be targeted; and outputting the generated notification to the platforms on which the user consents to be targeted.

Abstract: A method includes receiving inputs from a plurality of data providers reflecting the plurality of data providers' respective parameters for providing message channel data; receiving inputs from a plurality of data recipients reflecting the data recipients' respective parameters for receiving message channel data; identifying, using a matching engine, message channel data that matches the parameters of at least one of the plurality of data providers and the parameters of at least one of the data recipients; processing the message channel data in accordance with the parameters of the data providers, the processing step comprising segmenting the message channel data into permitted data segments and non-permitted data segments based on the data providers' parameters; delivering the permitted data segments to the identified data recipients in accordance with their respective parameters; and initiating a request for compensation of the identified data providers in accordance with their respective parameters.

Abstract: The present teaching relates to communication related to predictions. A communication chain is created with multiple chain units, each operating independently to provide prediction services related to a prompt with embedded information therein associated with predictions for the prompt to enable prediction services. A request is received for a requested operation related to a query prompt on one of prediction solicitation, prediction entry, verification entry, and prediction access. If a chain unit for the query prompt, the request is directed to the chain unit to perform the requested operation. If not, a new chain unit is created for the query prompt and the request is forwarded to the new chain unit to carry out the requested operation.

Abstract: In an example, a starting argument post may be received, via a first debate interface, from a first client device associated with a first user account of a debate system. A first response post may be received, via a second debate interface, from a second client device associated with a second user account of the debate system. The first response post corresponds to a response to the starting argument post. The starting argument post and the first response post are included in a first debate thread. When a first submission status of the first user account is active, submission of a response post for inclusion in the first debate thread may be enabled via the first debate interface. A second response post may be received, via the first debate interface and when the first submission status of the first user account is active, from the first client device.

Abstract: Disclosed are systems and methods for initiating communication between users of a user group based on machine learning techniques. The disclosed systems and methods provide a novel framework for automating communication scheduling and communication initiation based on user communication objectives and machine learning techniques. The disclosed framework operates by leveraging available user provided communication parameters, user provided objectives, and various real-time data associated with the users, and using the aforementioned data as inputs for machine learning models, in order to schedule communication between the users, automatically initiate communication between the users, or transmit communication notifications to the users.

Abstract: Disclosed are systems and methods for initiating communication between users of a user group based on machine learning techniques. The disclosed systems and methods provide a novel framework for automating communication scheduling and communication initiation based on user communication objectives and machine learning techniques. The disclosed framework operates by leveraging available user provided communication parameters, user provided objectives, and various real-time data associated with the users, and using the aforementioned data as inputs for machine learning models, in order to schedule communication between the users, automatically initiate communication between the users, or transmit communication notifications to the users.

Abstract: A user device may invoke, for a user associated with an unavailable user device, a guest mode, and may connect the user device with a network device based on invoking the guest mode. The user device may provide credentials of the user and a secure input of the user to the network device based on invoking the guest mode, and may receive an identity service and an emergency service for the user when the secure input is authenticated by the network device. The user device may associate, via the identity service, the user with the user device to enable the user to utilize the emergency service, and may provide, via the emergency service, one or more emergency notifications. The user device may receive an indication of the user exiting the guest mode, and may remove the credentials of the user from a memory based on the indication.

Abstract: One or more computing devices, systems, and/or methods for providing comparable items for a query item are provided. A query is constructed based upon a set of similarity characteristics and a set of difference characteristics specified for a query item. The query is executed to identify a set of query item results comprising comparable items having characteristics similar to the set of similarity characteristics and characteristics different from the set of difference characteristics. The set of query item results are provided as query results for the query.

Abstract: A user device may invoke, for a user associated with an unavailable user device, a guest mode, and may connect the user device with a network device based on invoking the guest mode. The user device may provide credentials of the user and a secure input of the user to the network device based on invoking the guest mode, and may receive an identity service and an emergency service for the user when the secure input is authenticated by the network device. The user device may associate, via the identity service, the user with the user device to enable the user to utilize the emergency service, and may provide, via the emergency service, one or more emergency notifications. The user device may receive an indication of the user exiting the guest mode, and may remove the credentials of the user from a memory based on the indication.

Abstract: One or more computing devices, systems, and/or methods for implementing automated barriers and delays for communication are provided. Content generated by a user may be evaluated to classify the content before the content has been submitted for access by other users. A user interface is generated and populated with an activity for the user to perform based upon a classification of the content. The user may be restricted from submitting the content until successful performance of the activity. Upon determining that the user successfully performed the activity, the user may be provided with an option to submit the content. Otherwise, the user may be blocked from submitting the content.

Abstract: A user device may invoke, for a user associated with an unavailable user device, a guest mode, and may connect the user device with a network device based on invoking the guest mode. The user device may provide credentials of the user and a secure input of the user to the network device based on invoking the guest mode, and may receive an identity service and an emergency service for the user when the secure input is authenticated by the network device. The user device may associate, via the identity service, the user with the user device to enable the user to utilize the emergency service, and may provide, via the emergency service, one or more emergency notifications. The user device may receive an indication of the user exiting the guest mode, and may remove the credentials of the user from a memory based on the indication.

Abstract: One or more devices, systems, and/or methods for presenting real-time videos of views that are obstructed are provided. For example, a first video may be received from a first camera. The first video comprises a real-time representation of a view opposing a first side of an obstruction. The first video is processed using a set of video parameters to generate a second video. The second video is transmitted to a display device. The second video is displayed on a display area positioned on a second side of the obstruction. A third video, comprising a real-time representation of the display area, is received. The set of video parameters are modified to generate a modified set of video parameters, based upon a comparison of the third video with the first video. The first video is processed using the modified set of parameters to generate an updated instance of the second video.

Abstract: Disclosed are systems and methods for initiating communication between users of a user group based on machine learning techniques. The disclosed systems and methods provide a novel framework for automating communication scheduling and communication initiation based on user communication objectives and machine learning techniques. The disclosed framework operates by leveraging available user provided communication parameters, user provided objectives, and various real-time data associated with the users, and using the aforementioned data as inputs for machine learning models, in order to schedule communication between the users, automatically initiate communication between the users, or transmit communication notifications to the users.