A method, system and computer-usable medium are disclosed for computing file system management. A corpus of content is processed to extract metadata associated with folders and files referenced by a directory structure. Natural Language Processing (NLP) operations are then performed on the corpus to generate concept and entity data associated with each folder and file, followed by performing Natural Language (NL) classification operations to generate intent classification data, which in turn is processed. to determine ranked, dominant intents for each folder and file. The corpus content, extracted metadata, concept and entity data, and ranked dominant intents are then processed to generate indexed content and term data. Application context data associated with an interaction is collected and processed to determine a user intent, which is then processed with the indexed content and term data to identify a corresponding folder and file, which in turn are provided to the user.

Disclosed is a computer implemented data collection method and system. In one aspect the method includes: transferring a message indicative of a form question of a form via a communication service for presentation in a conversational format upon a data entry processing system; receiving, via the communication service, a response in a conversational format from the user operating the data entry processing system; attempting to interpret the response using an expert system; in the event that the response data is interpreted as an answer, recording the answer as part of form instance data; and in the event that the response cannot be interpreted by the expert system, facilitating a data collection user to conduct a portion of the data collection session via the data collection processing system, wherein input is subsequently received from the data collection user to continue interpreting further responses during the form collection session.

The present disclosure relates to methods and systems for querying data in a data repository. According to a first aspect, this disclosure describes a method of querying a database, comprising: receiving, at a computing device, a plurality of keywords; determining, by the computer device, a plurality of datasets relating to the keywords; identifying, by the computer device, metadata for the plurality of datasets indicating a relationship between the datasets by examining an ontology associated with the datasets; providing, by the computer device, one or more suggested database queries in natural language form, the one or more suggested database queries constructed based on the plurality of keywords and the metadata; receiving, by the computing device, a selection of the one or more suggested database queries; and constructing, by the computer device, an object view for the plurality of datasets based on the selected query and the metadata.

A system and method for processing data by accessing data sets for a plurality of variables in at least one data store; associating a plurality of the data sets as at least one variable type; storing in a data store a plurality of operation definitions defining a plurality of operations on at least one of said at least one variable type; receiving from a user interface a selection of at least one operation definition and at least one data set of said at least one variable type operated on by the selected at least one operation definition; and processing the at least one data set in response to the selection according to the at least one operation definition to generate a derived data set.

A control system includes an information processing device that communicates with a controller that controls a control target. The controller or the information processing device include a storage device that stores one or more SQL statements to be executed and an execution result the one or more SQL statements in association with each other as log data. The information processing device includes a display controller that displays on a display an SQL statement to be corrected that has an unsuccessful execution result; an operation unit that accepts a correction operation on the SQL statement and an execution operation; and a communication interface that sends an execution instruction to execute the corrected SQL statement to the controller upon receipt of the execution operation and to receive an execution result of the corrected SQL statement from the controller. The display controller displays an execution result of the corrected SQL statement.

Embodiments are directed to a method for determining an interview script in a claims submission. The method may comprising receiving data relating to a claim being submitted, which may include claims submission data input by a user, information relating to the user, and one or more features. Data associated with the one or more features may be determined from an artificial intelligence model. A first score based on the data associated with the one or more features and data associated with the information relating to the user may be determined and used to determine an interview script. In one embodiment, questions in the interview script may continue to be provided to the interviewer computer if a continually updated score remains above a predetermined threshold. In another embodiment, the user may be routed to a live interview with a human representative if a continually updated score drops below a predetermined threshold.

A system for format-agnostic document ingestion including a document ingestion server and a database is disclosed. The server is configured to receive an image of a document comprising text in an unknown format, convert the image, using OCR, into a plurality of text elements a content, a size, and an absolute position. The server is also configured to retrieve data detectors from the database, each associated with a data type anticipated to be in the document, and comprising at least one identifier and direction, and at least one validation criteria. The server is also configured to identify a potential descriptor by comparing the content of each text element with the at least one identifier, and then determine if the text element pointed to by the data detector meets the validation criteria. Finally, the server is configured to associate the validated text element with the data detector, and store the content.

A data server may support segment identification based on a selected user profile. For example, a user may select a user profile as the basis for identifying a segment of additional user profiles. The server may identify attributes associated with the selected user identifier and generate an expression based on the identified subset. The expression may include a normalization function corresponding to at least one attribute. The normalization function may identify correlated attribute values for an attribute associated with the selected user profile. The data server may query a data storage system to identify the additional user profiles based on the expression. The data server may also support user defined Boolean expressions such that the expression is used to identify user identifiers associated with a first attribute and a second attribute.

Systems and methods are described for processing ingested data in an asynchronous manner as the data is being ingested to detect potential anomalies. For example, one or more streaming data processors can convert data as the data is ingested into a comparable data structure, determine whether the comparable data structure should be assigned to an existing data pattern or a new data pattern, and optionally update a characteristic of the data pattern to which the comparable data structure is assigned. The streaming data processor(s) can perform these operations automatically in real-time or in periodic batches. Once one or more comparable data structures have been assigned to one or more data patterns, the streaming data processor(s) can analyze the comparable data structures assigned to a particular data pattern to determine whether any of the comparable data structures appear to be anomalous.

Systems and methods are described for processing ingested data in an asynchronous manner as the data is being ingested to detect potential anomalies. For example, one or more streaming data processors can convert data as the data is ingested into a comparable data structure, determine whether the comparable data structure should be assigned to an existing data pattern or a new data pattern, and optionally update a characteristic of the data pattern to which the comparable data structure is assigned. The streaming data processor(s) can perform these operations automatically in real-time or in periodic batches. Once one or more comparable data structures have been assigned to one or more data patterns, the streaming data processor(s) can analyze the comparable data structures assigned to a particular data pattern to determine whether any of the comparable data structures appear to be anomalous.