International Business Machines Corporation

Nicholas Todd Lawrence

Rafal Przemyslaw Konik

Sumit Patel

Kyle Gilbertson

David Bacarella

David S Charron

James H Barnebee, Iv

Jian Li

Robert J Bestgen

Xing Xing Shen

Fernando Jose Suarez Saiz

Yi Yuan

Robert L Nielsen

Kathryn Rose Steinbrink

Randy Keith Rolfe

Corey Sanders

Dag O Roppe

Jason John Spieth

A system and related method exchange medical information with a medical management system. The method comprises receiving, using a processor of a code point resolver, from the medical management system, medical text via a network interface. A code point is a single standardized medical terminology code (SMTC) that corresponds to a medical concept contained within the medical text. The method further applies rule-based logic to process the medical text to form a localized mapping of a text portion of the medical text to a plurality of candidate SMTCs (CSMTCs) that are related to at least one metathesaurus concept entity (MCE) in a metathesaurus, and to determines the code point from the CSMTCs. The method transmits, via the network interface, to the medical management system, the code point.

Code point resolution using natural language processing and metathesaurus

A system, computer program product, and method are provided to automate a framework for knowledge graph based persistence of data, and to resolve temporal changes and uncertainties in the knowledge graph. Natural language understanding, together with one or more machine learning models (MLMs), is used to extract data from unstructured information, including entities and entity relationships. The extracted data is populated into a knowledge graph. As the KG is subject to change, the KG is used to create new and retrain existing machine learning models (MLMs). Weighting is applied to the populated data in the form of veracity value. Blockchain technology is applied to the populated data to ensure reliability of the data and to provide auditability to assess changes to the data.

Machine learning model modification and natural language processing

An approach is described of structuring resources among a plurality of resources in a system architecture. A method pertaining to such approach may include accessing a knowledge base including attributes relevant to the plurality of resources. The attributes of the knowledge base may include concepts and logical relationships associated with the concepts. The method further may include, responsive to receiving at least one resource to be processed with respect to the plurality of resources, extracting characteristics from the at least one resource based upon the attributes of the knowledge base, and storing the extracted characteristics in a repository. The method further may include, responsive to an application request, creating a URI structure representing at least one matching resource among the plurality of resources that corresponds to the application request.

Creating a uniform resource identifier structure to represent resources

Machine learning to integrate knowledge and augment natural language processing

Machine learning modification and natural language processing

A system, computer program product, and method are provided to automate a framework for knowledge graph based persistence of data, and to resolve temporal changes and uncertainties in the knowledge graph. Natural language understanding, together with one or more machine learning models (MLMs), is used to extract data and a data relationship from structured and/or unstructured data, create an entry in the KG and selectively store the extracted data and data relationship in the KG, assign a veracity value to the stored data, create an asset value entry in a corresponding BC ledger, and store a BC identifier with the KG entry.

Machine learning to integrate knowledge and natural language processing

A method for dynamically and cognitively generating and delivering web build layers for web applications is provided. The method may include receiving, by a computer, file requests associated with web applications. The method may further include, in response to receiving the file requests, identifying resource files associated with the file requests and the web applications by querying, by a computer, at least one application server for the resource files. Additionally, the method may include determining, by a computer, related resource files based on the identified resource files by tracking information and user activity associated with the identified resource files. The method may also include generating web build layers by grouping, by a computer, the determined related resource files. The method may further include delivering the generated optimized web build layers to the web applications based on the tracked information and user activity.

Dynamic cognitive optimization of web applications

Disclosed aspects include a temporal relational database management system initiating a set of operations. A set of columns in a transaction time temporal table is identified for change categorization. A change categorization model is constructed. The change categorization model is based on a set of changes with respect to the set of columns in the transaction time temporal table. The change categorization model uses a cluster analysis technique. Based on the change categorization model, a group of change categories for a set of rows coupled with the set of columns in the transaction time temporal table is determined. Based on the change categorization model, a first change category of the group of change categories is established in a first row of the set of rows.

Managing data within a temporal relational database management system

A method, system and computer program product are provided for implementing automatic access control list validation using automatic categorization of unstructured text. Automatic categorization of unstructured text is performed on a plurality of documents of an access control list for determining an average term vector. Each of the documents is scored against the average term vector to identify a dissimilar document, flagged as a possible security risk. Automatic categorization of unstructured text is performed on user information of a plurality of members of a candidate access control list for determining a typical term vector. A similarity score is determined by user information and the typical term vector, members of an access control list that are dissimilar from other members of the access control list are identified.

Implementing automatic access control list validation using automatic categorization of unstructured text

Systems and methods are provided for handling synchronous requests from a requesting entity. Illustratively, the requesting entity is in a database management system and the requests are made to a catalog server. The catalog server is configured to respond to the requests by accessing a catalog database. An interface is provided between an application and a catalog server. The interface is configured to determine whether the catalog server is available to handle requests. If the catalog server is unavailable and if the request is a synchronous request, the interface determines whether the request may be processed asynchronously.

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Rochester, MN, United States of America

Nicholas Todd Lawrence