A system for database access comprising a plurality of databases, each database having a plurality of defined data fields and a mapping system coupled to the plurality of databases, the mapping system configured to create an algorithmic relationship between a plurality of first fields of a plurality of first databases, and a corresponding field of a plurality of second fields of a plurality of second databases.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using frames for performing tasks. One of the methods includes receiving a first request to perform a task, the first request comprising user speech identifying the task; generating a frame associated with the task, wherein the frame comprises one or more types of values necessary to perform the task, and wherein each type of value can be satisfied by a respective value; receiving a second request to provide information related to a question, the second request comprising user speech identifying the question; providing information identifying the question to a search engine, and receiving a response identifying one or more terms; determining that at least one term can satisfy a type of value necessary to perform the task; and storing the at least one term in the frame.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using frames for performing tasks. One of the methods includes receiving a first request to perform a task, the first request comprising user speech identifying the task; generating a frame associated with the task, wherein the frame comprises one or more types of values necessary to perform the task, and wherein each type of value can be satisfied by a respective value; receiving a second request to provide information related to a question, the second request comprising user speech identifying the question; providing information identifying the question to a search engine, and receiving a response identifying one or more terms; determining that at least one term can satisfy a type of value necessary to perform the task; and storing the at least one term in the frame.

Embodiments of the present disclosure may include a method for credit underwriting, the method including receiving a dataset of user details. Embodiments may also include creating a convolutional neural network (CNN) with the dataset of user details. In some embodiments, the convolutional neural network organizes at least a portion of the dataset of user details into a layered and weighted dataset. Embodiments may also include creating an enriched layered and weighted dataset. Embodiments may also include executing a back-propagation operation to remove at least a portion of the layered and weighted data from the layered and weighted dataset. Embodiments may also include receiving a plurality of enriched layered and weighted datasets.

Embodiments of the present disclosure may include a method for credit underwriting, the method including receiving a dataset of user details. Embodiments may also include creating a convolutional neural network (CNN) with the dataset of user details. In some embodiments, the convolutional neural network organizes at least a portion of the dataset of user details into a layered and weighted dataset. Embodiments may also include creating an enriched layered and weighted dataset. Embodiments may also include executing a back-propagation operation to remove at least a portion of the layered and weighted data from the layered and weighted dataset. Embodiments may also include receiving a plurality of enriched layered and weighted datasets.

The present disclosure relates to systems, methods, and non-transitory computer readable media that utilize collaborative filtering and a reinforcement learning model having an actor-critic framework to provide digital content items across client devices. In particular, in one or more embodiments, the disclosed systems monitor interactions of a client device with one or more digital content items to generate item embeddings (e.g., utilizing a collaborative filtering model). The disclosed systems further utilize a reinforcement learning model to generate a recommendation (e.g., determine one or more additional digital content items to provide to the client device) based on the user interactions. In some implementations, the disclosed systems utilize the reinforcement learning model to analyze every negative and positive interaction observed when generating the recommendation. Further, the disclosed systems utilize the reinforcement learning model to analyze item embeddings, which encode the relationships among the digital content items, when generating the recommendation.

In an aspect, an interactive electronic map module displays, from a screen, a geographical layout that includes land area divided into zip code regions defined by respective zip codes. Responsive to user selection in the land area, the selected zip code region is highlighted. Online dating candidates are filtered based on location within the selected zip code region. In another aspect, the module is configured for: a) interactively with the user, drawing for display a continuous line by, starting from a starting point, advancing to a current ending point; b) in real time, detecting user disengagement from the drawing; and c) responsive to detecting disengagement, highlighting display of the at least one enclosed area that was formed if the starting and current ending points are already connected or, if the starting and current ending points are not already connected, would be formed by connecting the points with a straight line. Filtering is based on location within an enclosed area. A surviving candidate's real-life likeness is displayed at his/her map location. Location identifying labels are removed/withheld from display by area/region or based on proximity to a surviving candidate.

In an aspect, an interactive electronic map module displays, from a screen, a geographical layout that includes land area divided into zip code regions defined by respective zip codes. Responsive to user selection in the land area, the selected zip code region is highlighted. Online dating candidates are filtered based on location within the selected zip code region. In another aspect, the module is configured for: a) interactively with the user, drawing for display a continuous line by, starting from a starting point, advancing to a current ending point; b) in real time, detecting user disengagement from the drawing; and c) responsive to detecting disengagement, highlighting display of the at least one enclosed area that was formed if the starting and current ending points are already connected or, if the starting and current ending points are not already connected, would be formed by connecting the points with a straight line. Filtering is based on location within an enclosed area. A surviving candidate's real-life likeness is displayed at his/her map location. Location identifying labels are removed/withheld from display by area/region or based on proximity to a surviving candidate.

A customized social media feed generation system enables users to create multiple curated social media feeds based on user-specified criteria. A digital content curation system receives user requests, obtains associated digital content form a social media platform, without requiring user intervention. The digital content is passed to the user's device and rendered in a news feed format that includes only the content specified by the user.

A customized social media feed generation system enables users to create multiple curated social media feeds based on user-specified criteria. A digital content curation system receives user requests, obtains associated digital content form a social media platform, without requiring user intervention. The digital content is passed to the user's device and rendered in a news feed format that includes only the content specified by the user.