Entigenlogic LLC

Bp Corporation North America Inc.

Ciba Specialty Chemicals Corporation

Stephen Chen

Gary W Grube

Frank John Williams

Andrew Chu

David Ralph Lazzara

Karl Olaf Knutson

Jessy Thomas

David Michael Corns, Ii

Donald Joseph Wurzel

Stephen Emerson Sundberg

Theodore Mazurkiewicz

Paige Kristen Thompson

Dennis Arlen Roberson

Eric Andrew Faurie

Thomas James MacTavish

Ameeta Vasant Reed

Paul J Cahill

Weilong L Chiang

Boh C Tsai

George E Rotter

Lakshmi N Venkateshwaran

Walter M Nyderek

Roman F Barski

David C Johnson

Donald F Ackerley

Weilong Chiang Chiang

A method includes determining a set of identigens for words of content to produce a sets of identigens and interpreting the sets of identigens to determine a most likely meaning interpretation of the content and produce a baseline entigen group. The method further includes recovering an incomplete entigen group for the topic from a first knowledge database based on a knowledge defect of the incomplete entigen group with regards to the topic. The method further includes obtaining an additive entigen group from a second knowledge database based on the knowledge defect and modifying the incomplete entigen group utilizing the additive entigen group to produce an updated entigen group to provide a beneficial cure for the knowledge defect of the incomplete entigen group.

Creating a superset of knowledge

A method performed by a computing device includes determining a set of identigens for each word of words of a product-service query to produce sets of identigens. The method further includes interpreting, using identigen pairing rules of a knowledge database, the sets of identigens to determine a most likely meaning interpretation of the product-service query and produce a query entigen group that includes query entigens. The method further includes identifying one or more characteristic entigen categories for a subjective category entigen of the query entigen group. The method further includes recovering a set of response entigens for the product-service query from the knowledge database utilizing the query entigen group and based on the one or more characteristic entigen categories. The set of response entigens provides an answer for the product-service query.

Generating a product-service query response utilizing a knowledge database

A method includes detecting an incomplete entigen group within a knowledge database. The incomplete entigen group includes entigens and one or more entigen relationships between at least some of the entigens. The incomplete entigen group represents knowledge of a topic. The method further includes obtaining additive content for the topic based on the incomplete entigen group and generating an additive entigen group based on the additive content. The method further includes updating the incomplete entigen group utilizing the additive entigen group to produce an updated entigen group. The method further includes indicating that the updated entigen group has an un-curated status when the additive entigen group conflicts with the incomplete entigen group.

Curating knowledge of a knowledge database

A method executed by a computing device includes determining whether a set of words are included in a word set. When the set of words are in the word set, the method further includes determining a set of identigens for each word of the word set to produce sets of identigens, where a set of identigens of the sets of identigens represents one or more different meanings of a word of the word set. The method further includes interpreting, using identigen pairing rules, the sets of identigens to produce an entigen set. The method further includes assigning a single new entigen to represent the entigen set, where the single new entigen represents a most likely meaning interpretation of the word set.

Assigning a single new entigen to a word set

A method executed by a computing device includes determining to update an entigen group within a knowledge database, where the entigen group includes a set of linked entigens that represent knowledge associated with an object. The method further includes determining a set of identigens for each word of a phrase associated with the object to produce sets of identigens. The method further includes interpreting the sets of identigens to determine a most likely meaning interpretation of the phrase and produce a new entigen group. The method further includes updating the entigen group utilizing the new entigen group to produce a curated entigen group such that a deficiency of the entigen group is resolved providing more accurate and more complete knowledge of the object.

Curing a deficiency of a knowledge database

A method for execution by a computing device includes obtaining a set of media element identigens for media elements of media to produce sets of media element identigens. The sets of media element identigens are possible interpretations of a media element. The method further includes generating a set of relationships between media elements. The relationships provide a list of one or more ways in which the media elements are related. The method further includes processing different permutations of the sets of media element identigens using the set of relationships to generate an entigen group. The entigen group represents a most likely interpretation of the media.

Interpreting media

A method executed by a computing device includes obtaining a string of words and determining whether two or more words of the string of words are in a word group. When the two or more words are in the word group, the method further includes determining a set of identigens for each word of the word group to produce sets of identigens, where a set of identigens of the sets of identigens represents one or more different meanings of a word of the word group. The method further includes interpreting, using identigen pairing rules, the sets of identigens to produce an entigen group. The method further includes assigning a new entigen to represent the entigen group, where the new entigen represents a most likely meaning interpretation of the word group.

Assigning a new entigen to a word group

A method includes generating a plurality of entigen groups from a plurality of phrases, where the plurality of entigen groups represents a plurality of most likely meanings for the plurality of phrases. The method further includes determining an initial interpretation of the related topic based on the plurality of most likely meanings for the plurality of phrases and generating a plurality of scores for the plurality of entigen groups based on the initial interpretation and source information of the plurality of phrases. The method further includes interpreting the plurality of scores in relation to the initial interpretation to determine a confidence level of the initial interpretation and when the confidence level of the initial interpretation compares favorably to a confidence threshold, indicating that the initial interpretation is reliable.

Curating knowledge for storage in a knowledge database

A method includes obtaining a string of words and determining whether two or more words of the string of words are in a word group. When the two or more words are in the word group, the method further includes retrieving a set of word group identigens for the word group and retrieving sets of word identigens for remaining words of the string of words. The method further includes determining whether a word group identigen of the set of word group identigens and word identigens of the sets of word identigens creates an entigen group that is a valid interpretation of the string of words. When the entigen group is the valid interpretation of the string of words, the method further includes outputting the entigen group.

Interpreting a meaning of a word string

A method includes detecting a defective entigen group within a knowledge database. The defective entigen group includes entigens and one or more entigen relationships between at least some of the entigens. The defective entigen group represents knowledge of a topic. The method further includes obtaining corrective content for the topic based on the defective entigen group and generating a corrective entigen group based on the corrective content. The method further includes updating the defective entigen group utilizing the corrective entigen group to produce a curated entigen group.

Remedying defective knowledge of a knowledge database

A method includes identifying a set of identigens for each word of a first phrase of a phrase group to produce a first plurality of sets of identigens and determining whether first and second identigen rules are applicable to the first plurality of sets of identigens. When the first and second identigen rules are applicable to the first plurality of sets of identigens, the method further includes identifying a set of identigens for each word of a second phrase of the phrase group to produce a second plurality of sets of identigens and determining that the first identigen rules are applicable to the second plurality of sets of identigens. The method further includes identifying one valid identigen of each set of identigens of the first plurality of sets of identigens by applying the first identigen rules to the first plurality of sets of identigens to produce a first entigen group.

Interpreting a most likely meaning of a phrase

A method includes generating a new entigen group regarding trusted new information. The method further includes generating entigen groups from phrases of a document and determining whether an entigen group of the entigen groups has a most likely meaning similar to a most likely meaning of the new entigen group. When the entigen group has a most likely meaning similar to the most likely meaning of the new entigen group, the method further includes updating the entigen group based on the new entigen group. When the entigen groups do not include an entigen group having a most likely meaning similar to the most likely meaning of the new entigen group, the method further includes updating the entigen groups to include the new entigen group.

Updating a document utilizing trusted new information

A method includes generating an initial entigen group for a query from existing entigens in a knowledge database and determining whether the initial entigen group provides a reliable response to the query. When the initial entigen group does not provide a reliable response to the query, the method further includes determining a desired entigen to add to the initial entigen group to produce an updated entigen group that leads to the reliable response to the query and creating the desired entigen based on obtained targeted data. The method further includes adding the desired entigen to the initial entigen group to produce the updated entigen group and determining whether the updated entigen group provides the reliable response to the query. When the updated entigen group provides the reliable response to the query, the method further includes outputting the reliable response.

Generating a reliable response to a query

A method includes obtaining a set of image segment identigens for each image segment of an image to produce sets of image segment identigens. The sets of image segment identigens are possible interpretations of an image segment. The method further includes generating a set of relationships between image segments. The relationships provide a list of one or more ways in which the image segments are related. The method further includes processing different permutations of the sets of image segment identigens in accordance with the set of relationships to generate an entigen group. The entigen group represents a most likely interpretation of the image.

Interpreting an image

A method includes generating a plurality of entigen groups from a set of phrases of a statement and identifying two plausible entigen groups based on a true meaning interpretation of the statement. The method further includes identifying a related entigen group based on a phrase of the statement and interpreting each of the two plausible entigen groups in light of the related entigen group to determine whether one of the two plausible entigen groups is a more likely interpretation of the statement than the other one of the two plausible entigen groups. When the one of the two plausible entigen groups is the more likely interpretation of the statement, the method further includes updating the one of the two plausible entigen groups using the related entigen group to produce an updated entigen group and adding the statement as the updated entigen group to a knowledge database.

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Wheaton, IL, United States of America

Stephen Chen