Patents by Inventor Lea A. Deleris
Lea A. Deleris 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: 11676134Abstract: Embodiments for entity transaction interaction analysis and summarization by a processor. Transaction elements relating to one or more entity transaction interactions may be identifies and extracted from one or more communications. The transaction elements may be combined with one or more transaction opportunities and transaction historical data to provide a transaction summary.Type: GrantFiled: June 17, 2019Date of Patent: June 13, 2023Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Elizabeth Daly, Léa Deleris, Martin Stephenson
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Patent number: 11593412Abstract: Various embodiments are provided for implementing an approximation nearest neighbour (ANN) search in a computing environment are provided. An approximation nearest neighbour (ANN) of a plurality of feature vectors in hyper-planes with dynamically variable subspaces by searching an inverted index may be retrieved.Type: GrantFiled: July 22, 2019Date of Patent: February 28, 2023Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Debasis Ganguly, Léa Deleris
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Patent number: 11586652Abstract: A data structure is used to configure and transform a computer machine learning system. The data structure has one or more records where each record is a (vector) representation of a selected object in a corpus. One or more non-zero parameters in the records define the selected object and the number of the non-zero parameters define a word length of the record. One or more zero-value parameters are in one or more of the records. The word length of the object representation varies, e.g. can increase, as necessary to accurately represent the object within one or more contexts provided during training of a neural network used to create the database, e.g. as more and more contexts are introduced during the training. A minimum number of non-zero parameters are needed and zero-value parameters can be clustered together and compressed to save large amounts of system storage and shorten execution times.Type: GrantFiled: May 18, 2020Date of Patent: February 21, 2023Assignee: International Business Machines CorporationInventors: Debasis Ganguly, Léa Deleris
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Patent number: 11194849Abstract: Embodiments for relationship graph expansion and extraction from a collection of unstructured text data by a processor. A query relating to one or more concepts may be received. The query may be expanded according to a logical reasoning operation and a domain ontology having a set of logical rules. A relationship graph between one or more concepts from a plurality of unstructured text data may be extracted based on an expanded query according to a domain ontology and the set of logical rules.Type: GrantFiled: September 11, 2018Date of Patent: December 7, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Yassine Lassoued, Lea Deleris, Radu Marinescu, Julien Monteil
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Publication number: 20210357433Abstract: A data structure is used to configure and transform a computer machine learning system. The data structure has one or more records where each record is a (vector) representation of a selected object in a corpus. One or more non-zero parameters in the records define the selected object and the number of the non-zero parameters define a word length of the record. One or more zero-value parameters are in one or more of the records, The word length of the object representation varies, e.g. can increase, as necessary to accurately represent the object within one or more contexts provided during training of a neural network used to create the database, e.g. as more and more contexts are introduced during the training. A minimum number of non-zero parameters are needed and zero-value parameters can be clustered together and compressed to save large amounts of system storage and shorten execution times.Type: ApplicationFiled: May 18, 2020Publication date: November 18, 2021Inventors: Debasis Ganguly, Léa Deleris
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Patent number: 11023681Abstract: Embodiments for co-reference resolution and entity linking from unstructured text data by a processor. Semantic co-references and mentions of one or more entities may be resolved occurring in unstructured text data by linking the one or more entities using a domain knowledge ontology.Type: GrantFiled: September 19, 2018Date of Patent: June 1, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Yassine Lassoued, Lea Deleris, Stephane Deparis, Killian Levacher, Charles A. Jochim, Yufang Hou, Elizabeth Daly
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Patent number: 11003716Abstract: Embodiments for discovery and analysis of interpersonal relationships from a collection of unstructured text data by a processor. A relationship between one or more entities and extracted text data from a plurality of unstructured text data may be identified such that the relationship includes a sentiment of the relationship, a type of relationship, temporal information, or a combination thereof. The one or more entities may be associated with a knowledge graph based on an ontology of concepts representing a domain knowledge. The extracted information and the identified relationship may be automatically aggregated into a multi-graph representation.Type: GrantFiled: January 10, 2017Date of Patent: May 11, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Francesca Bonin, Elizabeth M. Daly, Lea A. Deleris, Stephane Deparis, Yufang Hou, Charles A. Jochim, Yassine Lassoued
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Publication number: 20210026877Abstract: Various embodiments are provided for implementing an approximation nearest neighbour (ANN) search in a computing environment are provided. An approximation nearest neighbour (ANN) of a plurality of feature vectors in hyper-planes with dynamically variable subspaces by searching an inverted index may be retrieved.Type: ApplicationFiled: July 22, 2019Publication date: January 28, 2021Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Debasis GANGULY, Léa DELERIS
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Publication number: 20200394649Abstract: Embodiments for entity transaction interaction analysis and summarization by a processor. Transaction elements relating to one or more entity transaction interactions may be identifies and extracted from one or more communications. The transaction elements may be combined with one or more transaction opportunities and transaction historical data to provide a transaction summary.Type: ApplicationFiled: June 17, 2019Publication date: December 17, 2020Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Elizabeth DALY, Léa DELERIS, Martin STEPHENSON
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Patent number: 10832009Abstract: Embodiments for extraction and summarization of decision discussions of a communication by a processor. The decision elements may be grouped together according to similar characteristics. The decision elements may be linked, and sentiments of the discussion participants towards each of the decision elements may be analyzed. A summary of the plurality of the decision elements may be provided via an interactive graphical user interface (GUI) on one or more Internet of Things (IoT) devices. The summary of the decision elements may be linked to domain knowledge. The summary may be enhanced using a domain knowledge.Type: GrantFiled: January 2, 2018Date of Patent: November 10, 2020Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Francesca Bonin, Lea Deleris, Debasis Ganguly, Killian Levacher, Martin Stephenson
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Patent number: 10762297Abstract: Embodiments for semantic hierarchical grouping of short text fragments by a processor. Sub-terms are extracted from a plurality of input text fragments according to a lexical sub-term hierarchy. Each of the sub-terms in the lexical sub-term hierarchy are matched with concepts based on an ontology of concepts representing a domain knowledge. The input text fragments are automatically grouped into a hierarchy of concepts based on the matching and a semantical relationship between each concept and matching sub-term.Type: GrantFiled: August 25, 2016Date of Patent: September 1, 2020Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Lea A. Deleris, Yassine Lassoued
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Publication number: 20200089766Abstract: Embodiments for co-reference resolution and entity linking from unstructured text data by a processor. Semantic co-references and mentions of one or more entities may be resolved occurring in unstructured text data by linking the one or more entities using a domain knowledge ontology.Type: ApplicationFiled: September 19, 2018Publication date: March 19, 2020Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Yassine LASSOUED, Lea DELERIS, Stephane DEPARIS, Killian LEVACHER, Charles A. JOCHIM, Yufang HOU, Elizabeth DALY
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Publication number: 20200082016Abstract: Embodiments for relationship graph expansion and extraction from a collection of unstructured text data by a processor. A query relating to one or more concepts may be received. The query may be expanded according to a logical reasoning operation and a domain ontology having a set of logical rules. A relationship graph between one or more concepts from a plurality of unstructured text data may be extracted based on an expanded query according to a domain ontology and the set of logical rules.Type: ApplicationFiled: September 11, 2018Publication date: March 12, 2020Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Yassine LASSOUED, Lea DELERIS, Radu MARINESCU, Julien MONTEIL
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Patent number: 10366331Abstract: There is provided a method, a system and a computer program product for supporting a decision making process. The system receives a decision model from a decision maker, the decision model used for determining a solution to a decision problem based on attributes and uncertainties of the decision problem. The decision problem includes information about a plurality of outcome vectors that represent all possible outcomes and the uncertainties associated with the decision problem. The system determines whether the received decision model can be solved without receiving any preference information from the decision maker. The system receives partially specified preference information from the decision maker if the received decision model cannot be solved without any preference information. The system solves the decision model with the partially specified preference information. The system recommends, based on the solution, one or more decisions to the decision maker.Type: GrantFiled: January 27, 2016Date of Patent: July 30, 2019Assignees: International Business Machines Corporation, University College Cork—National University Of Ireleand, CorkInventors: Lea A. Deleris, Radu Marinescu, Abdul Razak, Peter Nicholas Wilson
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Publication number: 20190205395Abstract: Embodiments for extraction and summarization of decision discussions of a communication by a processor. The decision elements may be grouped together according to similar characteristics. The decision elements may be linked, and sentiments of the discussion participants towards each of the decision elements may be analyzed. A summary of the plurality of the decision elements may be provided via an interactive graphical user interface (GUI) on one or more Internet of Things (IoT) devices. The summary of the decision elements may be linked to domain knowledge. The summary may be enhanced using a domain knowledge.Type: ApplicationFiled: January 2, 2018Publication date: July 4, 2019Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Francesca BONIN, Lea DELERIS, Debasis GANGULY, Killian LEVACHER, Martin STEPHENSON
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Patent number: 10275730Abstract: A method and computer program product for extending a business process model.Type: GrantFiled: October 10, 2014Date of Patent: April 30, 2019Assignee: International Business Machines CorporationInventors: Eric W. Cope, Lea A. Deleris, Dominik Etzweiler, Jana Koehler, Jochen M. Kuester, Bonnie K. Ray
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Publication number: 20180197088Abstract: Embodiments for discovery and analysis of interpersonal relationships from a collection of unstructured text data by a processor. A relationship between one or more entities and extracted text data from a plurality of unstructured text data may be identified such that the relationship includes a sentiment of the relationship, a type of relationship, temporal information, or a combination thereof. The one or more entities may be associated with a knowledge graph based on an ontology of concepts representing a domain knowledge. The extracted information and the identified relationship may be automatically aggregated into a multi-graph representation.Type: ApplicationFiled: January 10, 2017Publication date: July 12, 2018Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Francesca BONIN, Elizabeth M. DALY, Lea A. DELERIS, Stephane DEPARIS, Yufang HOU, Charles A. JOCHIM, Yassine LASSOUED
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Publication number: 20180060305Abstract: Embodiments for semantic hierarchical grouping of short text fragments by a processor. Sub-terms are extracted from a plurality of input text fragments according to a lexical sub-term hierarchy. Each of the sub-terms in the lexical sub-term hierarchy are matched with concepts based on an ontology of concepts representing a domain knowledge. The input text fragments are automatically grouped into a hierarchy of concepts based on the matching and a semantical relationship between each concept and matching sub-term.Type: ApplicationFiled: August 25, 2016Publication date: March 1, 2018Applicants: INTERNATIONAL BUSINESS MACHINES CORPORATION, UNIVERSITY COLLEGE CORKInventors: Lea A. DELERIS, Yassine LASSOUED
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Patent number: 9829334Abstract: Embodiments of the disclosure include a method for journey planning including receiving a journey planning request, the journey planning request having an origin and a destination in a transportation network. The method also includes calculating an optimized journey plan by identifying a plurality of routes through the transportation network from the origin to the destination and determining an uncertainty associated with each of the plurality of routes. Calculating an optimized journey plan also includes evaluating a robustness of each of the plurality of routes to the uncertainty associated with each of the plurality of routes and selecting the optimized journey plan based on the journey planning request and the robustness of each of the plurality of routes.Type: GrantFiled: September 14, 2012Date of Patent: November 28, 2017Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Michele Berlingerio, Adi I. Botea, Eric P. Bouillet, Francesco Calabrese, Lea A. Deleris, Donna L. Gresh, Olivier Verscheure
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Patent number: 9652719Abstract: A system and computer program product that facilitates authoring of a Bayesian Belief Networks by: accessing text content stored in a content storage device; identifying statements within said accessed text content indicating a dependence relation; extracting said statements indicating said dependence relation from said text content; and aggregating said extracted statements into a form suitable for representation as a BBN network structure. To identify statements indicating a dependence relation, the system identifies one or more lexical and semantic attributes of variables within a text unit indicating a conditional dependence relation between two or more variables. The system further processes the text content to extract probabilistic information and probability statements and aggregate the probability statements into a quantitative layer of the BBN structure.Type: GrantFiled: September 17, 2013Date of Patent: May 16, 2017Assignee: SINOEAST CONCEPT LIMITEDInventors: Lamia T. Bounouane, Lea Deleris, Bogdan E. Sacaleanu, Brian F. White