Patents by Inventor Eman Omar
Eman Omar has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11087220Abstract: For confidence weighting relationships between complex entities in unstructured data an expressed relationship between a subset of a set of tokens is extracted from a knowledge graph corresponding to the unstructured data. The knowledge graph includes the set of tokens. The tokens in the subset of tokens are related in the expressed relationship by a set of predicates. A number of occurrences of the set of predicates in the unstructured data is determined. A number of occurrences of the expressed relationship in the unstructured data is determined. Using the number of occurrences of the set of predicates and the number of occurrences of the expressed relationship, a confidence value is computed and assigned to the expressed relationship.Type: GrantFiled: May 8, 2017Date of Patent: August 10, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Ahmed M. A. Nassar, Victoria O. Odeyemi, Eman Omar, Craig M. Trim
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Patent number: 10489442Abstract: A method, system, and computer program product for identifying related information in dissimilar data are provided in the illustrative embodiments. Using a first part of a first entry in a dictionary, a first portion is identified in a first data, the first part matching the first portion within a tolerance. A second part of the first entry referencing a section of a second data is determined, the second data being organized in a repository according to a schema. A third part of the first entry sufficient to locate a record in the section of the second data is determined. A query is constructed using the second part and the third part, and performed on the second data. A result set is obtained, wherein a record in the result set is related to the first portion in the first data and the record does not include the first portion.Type: GrantFiled: January 19, 2015Date of Patent: November 26, 2019Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Andrew R. Freed, Ahmed M. Nassar, Eman Omar, Craig M. Trim
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Publication number: 20170243118Abstract: For confidence weighting relationships between complex entities in unstructured data an expressed relationship between a subset of a set of tokens is extracted from a knowledge graph corresponding to the unstructured data. The knowledge graph includes the set of tokens. The tokens in the subset of tokens are related in the expressed relationship by a set of predicates. A number of occurrences of the set of predicates in the unstructured data is determined. A number of occurrences of the expressed relationship in the unstructured data is determined. Using the number of occurrences of the set of predicates and the number of occurrences of the expressed relationship, a confidence value is computed and assigned to the expressed relationship.Type: ApplicationFiled: May 8, 2017Publication date: August 24, 2017Applicant: International Business Machines CorporationInventors: Ahmed M.A. Nassar, Victoria O. Odeyemi, Eman Omar, Craig M. Trim
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Patent number: 9704104Abstract: For confidence weighting relationships between complex entities in unstructured data an expressed relationship between a subset of a set of tokens is extracted from a knowledge graph corresponding to the unstructured data. The knowledge graph includes the set of tokens. The tokens in the subset of tokens are related in the expressed relationship by a set of predicates. A number of occurrences of the set of predicates in the unstructured data is determined. A number of occurrences of the expressed relationship in the unstructured data is determined. Using the number of occurrences of the set of predicates and the number of occurrences of the expressed relationship, a confidence value is computed and assigned to the expressed relationship.Type: GrantFiled: February 20, 2015Date of Patent: July 11, 2017Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Ahmed M. A. Nassar, Victoria O. Odeyemi, Eman Omar, Craig M. Trim
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Patent number: 9569733Abstract: To extract relationships between complex entities from unstructured data, a parser parses, using an existing language model, the unstructured data to generate a parse tree. From the parse tree, a set of tokens is created. A token in the set of tokens includes a set of words found in the unstructured data. The set of tokens is inserted in the existing language model to form an enhanced language model. The unstructured data is re-parsed using the enhanced language model to create a knowledge graph. From the knowledge graph, a relationship between a subset of the set of tokens is extracted.Type: GrantFiled: February 20, 2015Date of Patent: February 14, 2017Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Ahmed M. A. Nassar, Victoria O. Odeyemi, Eman Omar, Craig M. Trim
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Publication number: 20160247087Abstract: To extract relationships between complex entities from unstructured data, a parser parses, using an existing language model, the unstructured data to generate a parse tree. From the parse tree, a set of tokens is created. A token in the set of tokens includes a set of words found in the unstructured data. The set of tokens is inserted in the existing language model to form an enhanced language model. The unstructured data is re-parsed using the enhanced language model to create a knowledge graph. From the knowledge graph, a relationship between a subset of the set of tokens is extracted.Type: ApplicationFiled: February 20, 2015Publication date: August 25, 2016Applicant: International Business Machines CorporationInventors: AHMED M.A. NASSAR, Victoria O. Odeyemi, Eman Omar, Craig M. Trim
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Publication number: 20160247088Abstract: For confidence weighting relationships between complex entities in unstructured data an expressed relationship between a subset of a set of tokens is extracted from a knowledge graph corresponding to the unstructured data. The knowledge graph includes the set of tokens. The tokens in the subset of tokens are related in the expressed relationship by a set of predicates. A number of occurrences of the set of predicates in the unstructured data is determined. A number of occurrences of the expressed relationship in the unstructured data is determined. Using the number of occurrences of the set of predicates and the number of occurrences of the expressed relationship, a confidence value is computed and assigned to the expressed relationship.Type: ApplicationFiled: February 20, 2015Publication date: August 25, 2016Applicant: International Business Machines CorporationInventors: Ahmed M.A. Nassar, Victoria O. Odeyemi, Eman Omar, Craig M. Trim
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Publication number: 20160210314Abstract: A method, system, and computer program product for identifying related information in dissimilar data are provided in the illustrative embodiments. Using a first part of a first entry in a dictionary, a first portion is identified in a first data, the first part matching the first portion within a tolerance. A second part of the first entry referencing a section of a second data is determined, the second data being organized in a repository according to a schema. A third part of the first entry sufficient to locate a record in the section of the second data is determined. A query is constructed using the second part and the third part, and performed on the second data. A result set is obtained, wherein a record in the result set is related to the first portion in the first data and the record does not include the first portion.Type: ApplicationFiled: January 19, 2015Publication date: July 21, 2016Applicant: International Business Machines CorporationInventors: Andrew R. Freed, Ahmed M. Nassar, Eman Omar, Craig M. Trim
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Publication number: 20160063095Abstract: A method, system, and computer program product for unstructured data guided query modification are provided in the illustrative embodiments. A set of parameters is identified in a structured database query. Using a Natural language processing (NLP) engine, a set of tokens is identified in an unstructured data. Using the NLP engine, corresponding to a subset of the set of parameters, sets of variations are obtained. A fit is found between a first token from the set of tokens and a first variant of a first parameter, the first variant of the first parameter being a member of a first set of variations corresponding to the first parameter. The first parameter in the structured database query is substituted with the first variant to produce a substituted query, wherein the substituted query produces a result set that is related to the unstructured data.Type: ApplicationFiled: August 27, 2014Publication date: March 3, 2016Inventors: AHMED M.A. NASSAR, Eman Omar, Evelyn M. Rosengarten, Craig M. Trim