Abstract: The present disclosure provides methods, apparatus, systems, computing devices, and/or the like for performing risk prediction by receiving outer cohort definition data and inner cohort definition data, the outer cohort definition data representative of a target data domain with respect to a dataset, and the inner cohort definition data representative of a prediction feature with respect to the target data domain, determining one or more inner cohort features based at least in part on a knowledge graph data object using the inner cohort definition data, the knowledge graph data object including co-occurrence information of features from the dataset, and generating, using a predictive machine learning model, for each of one or more outer cohort entities associated with features in an outer cohort data subset, a risk score representative of a propensity of the outer cohort entity being an inner cohort entity associated with features in an inner cohort data subset.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing risk score generation predictive data analysis. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform risk score generation predictive data analysis by utilizing at least one of event-based confidence scores and delay-based confidence scores.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing risk score generation predictive data analysis. Certain embodiments of the present invention utilize systems, methods, and computer program products that risk score generation predictive data analysis by utilizing at least one of inferred hybrid risk score generation machine learning models and hybrid graph-based machine learning models.

Abstract: Document retrieval from a large document storage database may be facilitated through the use of a search system configured for identifying concepts related to a specific search query provided by a user. Prior to retrieving documents for inclusion in a listing of search results, the terms included within a user-provided search query may be expanded based on relationships between terms represented within a Resource Description Framework (RDF) triplestore to generate a semantic search query. Documents linked with one or more of the terms included within the semantic search query are identified and included within the search results.

Abstract: Document retrieval from a large document storage database may be facilitated through the use of a search system configured for identifying concepts related to a specific search query provided by a user. Prior to retrieving documents for inclusion in a listing of search results, the terms included within a user-provided search query may be expanded based on relationships between terms represented within a Resource Description Framework (RDF) triplestore to generate a semantic search query. Documents linked with one or more of the terms included within the semantic search query are identified and included within the search results.