Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives a structured document. The structured document includes a string of characters. The program further traverses a hierarchy of concepts that includes a plurality of nodes and a plurality of edges connecting the plurality of nodes. Each node in the plurality of nodes represents a concept. Based on the traversal of the hierarchy, the program also identifies a set of concepts in the hierarchy of concepts. A concept in the set of concepts matches a subset of the string of characters. The program further generates a document profile for the structured document. The document profile includes a set of mappings. Each mapping in the set of mappings specifies an identifier associated with the structured document and an identifier associated with a concept in the set of concepts.

Abstract: The present disclosure pertains to computer readable documents including structured data content for visualizing a structure with a plurality of structure elements and a plurality of relationships between the plurality of structure elements. The document includes the structured data content, a data type indicator, and a structure type indicator. The data type indicator is used to determine a parsing algorithm, The parsing algorithm and the structure type indicator are used to parse the structured data content to determine the structure elements and the relationships between the structure elements. The lexical structure of the structured data content reflects the relationships between the structure elements. A visualization of the structure can be automatically generated. The visualization can be linked to or embedded within visualizations of other structures.

Abstract: The present disclosure pertains to computer readable documents including structured data content for visualizing a structure with a plurality of structure elements and a plurality of relationships between the plurality of structure elements. The document includes the structured data content, a data type indicator, and a structure type indicator. The data type indicator is used to determine a parsing algorithm, The parsing algorithm and the structure type indicator are used to parse the structured data content to determine the structure elements and the relationships between the structure elements. The lexical structure of the structured data content reflects the relationships between the structure elements. A visualization of the structure can be automatically generated. The visualization can be linked to or embedded within visualizations of other structures.

Abstract: In an example, a machine learning algorithm is used to train an entity risk evaluation model to output an entity risk score based on transaction data in a computer network. Entity risk scores for various entities may be stored in a database, and retrieved and displayed upon user interaction with one or more reports involving corresponding entities.

Abstract: In an example, a machine learning algorithm is used to train an entity risk evaluation model to output an entity risk score based on transaction data in a computer network. Entity risk scores for various entities may be stored in a database, and retrieved and displayed upon user interaction with one or more reports involving corresponding entities.

Abstract: A touch screen keyboard is described. Consistent with some embodiments, the touch screen keyboard derives a data pair representing the position of a detected finger press on a touch screen display relative to the position of a detected palm. This relative data is then compared against a set of reference data to identify an intended key press.