International Business Machines Corporation

Servicenow, Inc.

Robert L Nielsen

Andrew Ronald Freed

Corville O Allen

Roberto Delima

Ronald Bruce Baker

Ling-Ching W Tai

Joshua S Allen

Bradford Austin Fisher

Bryan M Ellington

Jacob E Yackenovich

Eric Woods

Fernando Jose Suarez Saiz

Jeffery Lake Crume

Nicholas Todd Lawrence

Nicholas V Bruno

Pamela D Andrejko

Jared M D Smythe

Saeid Sakhitab

Cynthia M Murch

Jan M Nordland

Humberto R Rivero

Corey Sanders

Steven M Golberg

Sandra L Benedict

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 method and system for determining a location of origin and a time period in which a document was written is disclosed. A text is received and a set of linguistic characteristics for the text are identified. A set of possible locations and time periods for the text are determined based on the set of linguistic characteristics. A set of reference documents are used to determine a proximity rating for the text based upon a determination of how close the text is to the reference documents. The potential locations and time periods are ranked and returned for presentation.

Linguistic based determination of text location origin

A method includes receiving a text and identifying a set of linguistic characteristics contained in the text, where linguistic characteristics include grammatical, syntactic, and idiomatic features of the text. The method also includes determining a plurality of locations of origin in which the text was potentially written based on the set of linguistic characteristics. The method also includes retrieving a set of reference documents for each location of origin in the plurality of locations of origin and producing a set of proximity scores by performing a set of proximity checks using the set of linguistic characteristics, the set of reference documents, and the text, wherein the proximity checks analyze how often and how close linguistic characteristics are to one another. The method also includes ranking the plurality of locations of origin based on the set of proximity scores and returning a set of one or more ranked locations of origin.

A method includes receiving a text. The method also includes identifying a set of linguistic characteristics contained in the text. The method also includes determining a plurality of time periods in which the text was potentially written based on the set of linguistic characteristics. The method also includes retrieving a set of reference documents for each time period. The method also includes producing a set of proximity scores by performing a set of proximity checks using the set of linguistic characteristics, the set of reference documents, and the text, where the proximity checks analyze how often and how close linguistic characteristics are to one another. The method also includes ranking the plurality of time periods based on the set of proximity scores and returning a set of one or more ranked time periods of the plurality of time periods.

Linguistic based determination of text creation date

Test cases for a text annotator are generated by determining types of inputs to the annotator and analyzing language structures in a corpus to identify sentence types and grammar constructs. An input type can correspond to multiple grammar constructs. Test cases are generated by performing grammar tree transformations on selected fragments from the corpus based on the sentence types and the grammar constructs. Additional test cases are generated by replacing starting phrases in selected fragments with substitute phrases from dictionaries associated with the input types (a dictionary can include a false synonym for an input type for purposes of negative testing). The two generating approaches can be combined, i.e., performing one or more successive (different) grammar tree transformations to yield a sentence which is then subjected to phrase substitution.

Generating natural language text sentences as test cases for NLP annotators with combinatorial test design

Mechanisms are provided for processing logical relationships in natural language content. A logical parse of a first parse of a natural language content is generated by identifying latent logical operators within the first parse indicative of logical relationships between elements of the natural language content. The logical parse comprises nodes and edges linking nodes. At least one knowledge value is associated with each node in the logical parse. The at least one knowledge value of at least a subset of the nodes in the logical parse is propagated to one or more other nodes in the logical parse based on propagation rules. A reasoning operation is performed on the logical parse to generate a knowledge output indicative of knowledge associated with one or more of the logical relationships between elements of the natural language content.

Natural language processing utilizing propagation of knowledge through logical parse tree structures

A method, system and apparatus for estimating an SLA breach value. The method can include processing resource data to identify an acceptable SLA breach value; and, displaying the acceptable SLA breach value through a user interface. The processing step can include identifying a best practices SLA breach value based upon resource data for an aggregation of customers. Alternatively, the processing step can include identifying an average SLA breach value for a specific customer. As a further alternative, the identifying step can include identifying an average SLA breach value for a specific customer for a specific resource. As yet a further alternative, the processing step can include identifying an SLA breach value trend based upon past measured historical systems management data; and, predicting a future SLA breach value based upon the trend. In all cases, the acceptable SLA breach value can be increased by a fixed proportion.

Autonomic SLA breach value estimation

A Configuration Management DataBase (CMDB) is utilized to reconcile names of enterprise computer resources in a Configuration Management Database (CMDB). Steps taken include creating a resource that belongs to a class that has multiple naming rules; in response to determining that more than one set of naming attributes is provided by the multiple naming rules, generating a set of valid names, in a priority order, for the resource; and correlating different names for the resource by, in accordance with the priority order, assigning one name for the resource to be a master name and assigning all other names for the resource to be alias names.

Resource name reconciliation in a configuration database

In a focal point network, adjacent nodes may agree to a relationship where one node (a focal point or server node) supplies network management services to the other node (a non-focal point or served node). A served node forwards management services data to its server node without waiting for any request. There is a risk that the nodes will become configured into a closed loop within which data, once introduced, will circulate endlessly. To eliminate this risk, a loop-detection message is generated when a node acquires a new server node and is itself a server node for other nodes. The message, which includes the originating node's name, is passed from served node to server node. Each node inspects the message. If it does not find its own name, it appends its name to the message and passes it on to its own server node. If the node does find its own name, it generates a loop-detected message that revokes the server/served relationship with the current server node.

Growing community of inventors

Chapel Hill, NC, United States of America

Robert L Nielsen