Abstract: Systems and methods of generating a personalized study plan with remedial content are disclosed. A first interface is generated including one or more sets of interface elements. The first interface allows selection of one interface element in each of the one or more sets of interface elements. The selected one interface element for each of the one or more sets of interface elements and a set of user preferences is obtained. Each of the selected one interface element is associated with the one or more factors including a tag and a semantic text. One or more opportunity areas based on the set of answers of the user data is determined and a plurality of content based on the one or more factors is identified. A second interface is generated. The second interface is comprised of one or more study features based on the one or more opportunity areas, the plurality of content, and the set of user preferences of the user.

Abstract: Systems and methods of searching content using one or more machine learning models are disclosed. In response to a user query request, a user query is received at a first user interface. One or more search terms are determined using a query parser based on the user query. One or more semantically similar queries are determined based on the one or more search terms. In accordance with a determination that the user query and the one or more semantically similar queries have not been previously searched, search for information related to the one or more search terms from one or more databases using the one or more machine learning models. An output to the user query is generated based on the information. The output includes at least a portion of the information and one or more citations associated with the information. The output is displayed at the first user interface.

Abstract: The present disclosure relates to methods and systems for ingesting content from data feeds and to generate an enhanced output of relevant content for presentation to a user to facilitate analysis of the relevant content. Content is received from data feeds, and filtered to identify relevant content with respect to a particular context. The relevant content is then processed, e.g., using natural language processes, to extract entities involved, and to also identify particular activities detailed in the relevant content. Activity-mining is applied to the identified relevant data to classify and assigned activity tags to the extracted entity. Based on the extracted and identified information, an enhanced output is generated for presentation to facilitate research operations. The enhanced output may include overlaid graphical annotations, indicators, and graphical controls over the relevant articles to provide a means for updating a database based on the relevant content.

Abstract: Described herein are systems and methods for an entity ranking system. In one embodiment, a computing system is configured to interface with one or more domains to identify a set of entities. The computing system can ascertain a first set of data components for each entity, normalize each of the first set of data components for each entity, and detect a failure to ascertain a second set of data components. The computing system can compute a statistical probability for a possible set of values for each data component of the second set based on the ascertained first set of data components. The computing system can rank each entity based on a derived quantile. The computing system can generate a graphical user interface including a visualization of the ranking of each entity, which can be rendered on a display of the at least one user computing devices.

Abstract: The present disclosure relates to methods and systems for ingesting content from data feeds and to generate an enhanced output of relevant content for presentation to a user to facilitate analysis of the relevant content. Content is received from data feeds, and filtered to identify relevant content with respect to a particular context. The relevant content is then processed, e.g., using natural language processes, to extract entities involved, and to also identify particular activities detailed in the relevant content. Activity-mining is applied to the identified relevant data to classify and assigned activity tags to the extracted entity. Based on the extracted and identified information, an enhanced output is generated for presentation to facilitate research operations. The enhanced output may include overlaid graphical annotations, indicators, and graphical controls over the relevant articles to provide a means for updating a database based on the relevant content.

Abstract: Described herein are systems and methods for an entity ranking system. In one embodiment, a computing system is configured to interface with one or more domains to identify a set of entities. The computing system can ascertain a first set of data components for each entity, normalize each of the first set of data components for each entity, and detect a failure to ascertain a second set of data components. The computing system can compute a statistical probability for a possible set of values for each data component of the second set based on the ascertained first set of data components. The computing system can rank each entity based on a derived quantile. The computing system can generate a graphical user interface including a visualization of the ranking of each entity, which can be rendered on a display of the at least one user computing devices.