Systems, methods, and non-transitory computer-readable media can provide a content feed having at least a first content item and a second content item through a display interface. The first content item can be associated with a threshold playback time. A determination can be made that the first content item is being played through the display interface. At least one touch screen gesture can be received through the display interface. A response to the touch screen gesture can be prevented until the first content item is played for the threshold playback time.

Described herein is a system for using a machine learning model to predict a metric value indicative of quality of user experience. The system can receive an indication that a mobile device was used to access electronic content. The system obtains a set of characteristics of a user of the mobile device and generates a predicted metric value indicative of a quality of user experience interacting with the electronic content by applying a trained machine learning model to the obtained set of characteristics. The machine learning model is trained on cluster data representing clusters of users of the system, and each cluster is associated with a one or more shared characteristics of users in the cluster and an average metric value selected by users in the cluster. The system selects and transmit an interactive element associated with the predicted metric value to the mobile device.

A computer implemented method for the automated analysis or use of data is implemented by a voice assistant. The method comprises the steps of: (a) storing in a memory a structured, machine-readable representation of data that conforms to a machine-readable language (machine representation); the machine representation including representations of user speech or text input to a human/machine interface; and (b) automatically processing the machine representations to analyse the user speech or text input.

A computer implemented method for the automated analysis or use of data is implemented by a voice assistant. The method comprises the steps of:(a) storing in a memory a structured, machine-readable representation of data that conforms to a machine-readable language (machine representation); the machine representation including representations of user speech or text input to a human/machine interface; and (b) automatically processing the machine representations to analyse the user speech or text input.

The present disclosure describes a communication system that includes communication circuitry and processing circuitry. The processing circuitry is configured to collect a piece of user information of a user via the communication circuitry, analyze the collected piece of user information to obtain a user preference of the user, and identify a piece of advertisement as targeting the user according to the user preference. The processing circuitry is further configured to generate a guidance message based on reason of promotion information stored in association with the piece of advertisement, transmit the guidance message to a client terminal of the user, and transmit the piece of advertisement to the client terminal. The guidance message and the piece of advertisement are to be output as vocalized speeches of a voice agent of the client terminal.

The present invention provides a product description support system executed by a computer system including a management server. This system includes an access reception unit that receives access using an identifier (e.g., URL) associated with a product; a content change unit that modifies content data associated with the identifier based on predetermined provision conditions; a content transmission unit that delivers the modified content to the user's terminal for display; and an access history management unit that records the provision history of the content. The content change unit selects content data by adopting one of various methods, such as evaluating access counts, user levels, elapsed time, viewing duration, or regional information, to tailor content to specific user conditions. The system enables dynamic content adaptation for enhanced user engagement, utilizing criteria like product sales regions, customer attributes, and past behavior to optimize the delivery of relevant product information.

A computer implemented method for the automated analysis or use of data is implemented by a voice assistant. The method comprises the steps of: (a) storing in a memory a structured, machine-readable representation of data that conforms to a machine-readable language (machine representation); the machine representation including representations of user speech or text input to a human/machine interface; and (b) automatically processing the machine representations to analyse the user speech or text input.

A computer implemented method for the automated analysis or use of data is implemented by a voice assistant. The method comprises the steps of: (a) storing in a memory a structured, machine-readable representation of data that conforms to a machine-readable language (machine representation); the machine representation including representations of user speech or text input to a human/machine interface; and (b) automatically processing the machine representations to analyse the user speech or text input.

A performance optimization system (POS) includes: a POS data platform configured to store data usable to determine the POS score; a machine learning platform configured to use machine learning to determine the POS score, the machine learning platform operably connected to the POS data platform; a prediction server operably connected to the machine learning platform, the prediction server comprising a server configured to receive an advertisement request from a client demand-side platform (DSP), the prediction server further configured to create a prediction request from the advertisement request, the prediction server further configured to score the prediction request to determine a likelihood to influence an end user by exposing the end user to the brand advertisement; and a prediction request log operably connected to the prediction server, the prediction request log configured to log the scored prediction request.

Embodiments provide a social networking platform offering various services, such as, facilitating aggregation and management of a user's interaction on one or more social networking platforms, offering enhanced control over the level of privacy associated with the flow of user data, offering tools to customize the user's exposure to advertisement-related content on the social networking platform(s), integrating features to control aspects of how data/content is presented to and visualized by the user, empowering the user to multicast direct messages to other users without the other users having to meet certain constraints, empowering the user to create and/or join a group based on messaging threads, and the like. One or more of these enhanced services/features are associated with a powerful framework of authentication/permission model for access control.