David P Contreras

US Patent:

8612963, Dec 17, 2013

Filed:

Dec 2, 2010

Appl. No.:

12/958558

Inventors:

Brendan C. Bull - Durham NC, US
David Contreras - Apex NC, US
Robert C. Sizemore - Fuquay-Varina NC, US

Assignee:

International Business Machines Corporation - Armonk NY

International Classification:

G06F 9/44
G06F 9/445

US Classification:

717168, 717175, 717177

Abstract:

Techniques are disclosed for deploying an application. In one embodiment, a packaging tool determines that an error exists in a packaged application. The packaging tool may guide a user in fixing the error by updating the packaging tool and repackaging the application using the updated packaging tool. The packaging tool may guide the user via one or more notifications output for display to the user.

US Patent:

20200394267, Dec 17, 2020

Filed:

Jun 11, 2019

Appl. No.:

16/437129

Inventors:

- Armonk NY, US
David Contreras - Willow Spring NC, US
Roberto Delima - Apex NC, US
Corville O. Allen - Morrisville NC, US

International Classification:

G06F 17/27
G06T 11/20
G06N 20/00

Abstract:

Aspects of the present disclosure relate to identifying semantic relationships. Natural language content is received. A part of speech is determined for respective terms within the natural language content. A semantic type is determined for each of two or more terms within the natural language content. A parse tree representation containing a plurality of nodes is then generated based on the natural language content, each of the plurality of nodes corresponding to at least one term within the natural language content, wherein visual characteristics of respective nodes of the plurality of nodes within the parse tree representation depend on the part of speech and semantic type of the respective terms. A bounding box identifying a semantic relationship is then generated around a set of nodes on the parse tree representation, the set of nodes including the two or more terms.

US Patent:

20200387571, Dec 10, 2020

Filed:

Jun 6, 2019

Appl. No.:

16/434112

Inventors:

- Armonk NY, US
Andrew R. Freed - Cary NC, US
Brien Muschett - Palm Beach Gardens FL, US
Krishna Mahajan - Raleigh NC, US
David Contreras - Willow Spring NC, US

International Classification:

G06F 17/27
G06F 17/24
G06N 5/02

Abstract:

A method, computer system, and a computer program product for relevancy-based document quality assessment is provided. The present invention may include computing a document quality score based on at least one container relevancy score determined based on at least one domain link to a domain knowledge base.

US Patent:

20200387572, Dec 10, 2020

Filed:

Jun 4, 2019

Appl. No.:

16/430427

Inventors:

- Armonk NY, US
Roberto Delima - Apex NC, US
David Contreras - Willow Spring NC, US
Krishna Mahajan - Raleigh NC, US

International Classification:

G06F 17/27
G06F 17/28
G06N 20/00

Abstract:

A method, system, and computer program product include providing a list of triggers, training the natural language processor with the list of triggers, providing to the natural language processor a text including one trigger, selecting nodes in the text to create an original potential span, predicting whether the original potential span includes another trigger, and adjusting, in response to predicting that the original potential span includes another trigger, the original potential span to exclude the another trigger to create a new potential span.

US Patent:

20200342053, Oct 29, 2020

Filed:

Apr 24, 2019

Appl. No.:

16/393145

Inventors:

- Armonk NY, US
David Contreras - Willow Spring NC, US
Roberto Delima - Apex NC, US
Corville O. Allen - Morrisville NC, US

International Classification:

G06F 17/27
G06F 17/22
G06N 3/08
G06N 20/00
G10L 15/26

Abstract:

Aspects of the present disclosure relate to identifying spans within unstructured electronic text. Natural language content is received. A part of speech and slot name of each word within the natural language content is identified. A parse tree representation is then generated based on the natural language content, wherein visual characteristics of each node of a plurality of nodes within the parse tree representation depend on the part of speech and slot name of each word. A bounding box identifying a span category is then generated around a set of nodes on the parse tree representation by a machine learning model.

US Patent:

20200334546, Oct 22, 2020

Filed:

Apr 17, 2019

Appl. No.:

16/386652

Inventors:

- Armonk NY, US
Andrew R. Freed - Cary NC, US
Roberto Delima - Apex NC, US
David Contreras - Willow Spring NC, US
Krishna Mahajan - Raleigh NC, US

International Classification:

G06N 5/02
G06F 16/93
G06F 16/908
G06F 17/27
G06N 20/00

Abstract:

An approach is provided that receives a document and a document type of the document. The document type identifies a document category to which the received document belongs. A set of linguistic metrics are retrieved that correspond to the document type. A quality of the received document is automatically determined based on a set of linguistic features found in the document as compared to the retrieved set of linguistic metrics. The document is then ingested into a corpus that is utilized by a question-answering (QA) system. The ingestion of the document is based on the determined quality.

US Patent:

20200311197, Oct 1, 2020

Filed:

Mar 27, 2019

Appl. No.:

16/366628

Inventors:

- Armonk NY, US
Roberto Delima - Apex NC, US
Chris Mwarabu - Holly Springs NC, US
David Contreras - Willow Spring NC, US
Kandhan Sekar - Durham NC, US
Krishna Mahajan - Raleigh NC, US

International Classification:

G06F 17/27
G06F 17/16

Abstract:

A phrase may be received that includes a plurality of tokens in a natural language format. A plurality of levels relating to dependencies between tokens of the plurality of tokens within the phrase is determined. A matrix structure is generated for the phrase. The matrix structure utilizes a plurality of rows and a plurality of columns to store data of the phrase. The plurality of rows and the plurality of columns each indicate one of an order of tokens of the plurality of tokens or levels of the plurality of levels.

US Patent:

20190318263, Oct 17, 2019

Filed:

Jun 26, 2019

Appl. No.:

16/453221

Inventors:

- Armonk NY, US
David Contreras - Willow Spring NC, US
Bob Delima - Apex NC, US
Corville O. Allen - Morrisville NC, US

International Classification:

G06N 20/00
G06F 17/27
G06F 16/33

Abstract:

Provided are a computer program product, system, and method for classifying text to determine a goal type used to select machine learning algorithm outcomes. Natural language processing of text is performed to determine features in the text and their relationships. A classifier classifies the text based on the relationships and features to determine a goal type. The determined features and relationships from the text are inputted into a plurality of different machine learning algorithms to generate outcomes. For each of the machine learning algorithms, a determination is made of performance measurements resulting from the machine learning algorithms generating the outcomes. A determination is made of at least one machine learning algorithm having performance measurements that are highly correlated to the determined goal type. An outcome is determined from at least one of the outcomes.