Patents by Inventor Jochen L. Leidner

Jochen L. Leidner 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).

  • Patent number: 10733380
    Abstract: A neural paraphrase generator receives a sequence of tuples comprising a source sequence of words, each tuple comprising word data element and structured tag element representing a linguistic attribute about the word data element. An RNN encoder receives a sequence of vectors representing a source sequence of words, and RNN decoder predicts a probability of a target sequence of words representing a target output sentence based on a recurrent state in the decoder. An input composition component includes a word embedding matrix and a tag embedding matrix, and receives and transforms the input sequence of tuples into a sequence of vectors by 1) mapping word data elements to word embedding matrix to generate word vectors, 2) mapping structured tag elements to tag embedding matrix to generate tag vectors, and 3) concatenating word vectors and tag vectors.
    Type: Grant
    Filed: May 14, 2018
    Date of Patent: August 4, 2020
    Assignee: THOMSON REUTERS ENTERPRISE CENTER GMBH
    Inventors: Jochen L. Leidner, Vasileios Plachouras, Fabio Petroni
  • Publication number: 20180329883
    Abstract: A neural paraphrase generator receives a sequence of tuples comprising a source sequence of words, each tuple comprising word data element and structured tag element representing a linguistic attribute about the word data element. An RNN encoder receives a sequence of vectors representing a source sequence of words, and RNN decoder predicts a probability of a target sequence of words representing a target output sentence based on a recurrent state in the decoder. An input composition component includes a word embedding matrix and a tag embedding matrix, and receives and transforms the input sequence of tuples into a sequence of vectors by 1) mapping word data elements to word embedding matrix to generate word vectors, 2) mapping structured tag elements to tag embedding matrix to generate tag vectors, and 3) concatenating word vectors and tag vectors.
    Type: Application
    Filed: May 14, 2018
    Publication date: November 15, 2018
    Applicant: Thomson Reuters Global Resources Unlimited Company
    Inventors: Jochen L. Leidner, Vasileios Plachouras, Fabio Petroni
  • Publication number: 20180197128
    Abstract: The present invention relates to a computer-based system for identifying supply chain risks and generating supply chain graphs representing an interconnected network of entities. An industrial graph database application is configured to account for direct and indirect (transitive) supplier risk and importance, based on a weighted set of measures: criticality, replaceability, centrality and distance. A graph-based model serves as an interactive and visual supply chain risk and importance explorer. A supply network is induced from textual data by applying text mining techniques to news stories and used to populate the supply chain/graph database.
    Type: Application
    Filed: December 6, 2017
    Publication date: July 12, 2018
    Applicant: Thomson Reuters Global Resources Unlimited Company
    Inventors: Lucas Carstens, Jochen L. Leidner, Krzysztof Szymanski, Blake Howald
  • Patent number: 9811518
    Abstract: Exemplary systems for processing a corpus of documents, such as legal contracts or agreements, are disclosed. The systems include a phrase discovery engine which derives statistics and phrase equivalence classes, groups of phrase equivalence classes, and uberphrases (clauses) bounded by phrases. These can be used to determine origins of phrases or clauses within given legal contract or to suggest alternative phrases and clauses.
    Type: Grant
    Filed: July 21, 2014
    Date of Patent: November 7, 2017
    Assignee: Thomson Reuters Global Resources
    Inventors: Jochen L. Leidner, Kingsley Martin, Trace Liggett, Gary Berosik, Thomas Zielund
  • Publication number: 20160371618
    Abstract: The present invention relates to a computer-based system for generating a risk register relating to a named entity. The system comprises a computing device, a risk database accessible by the computing device and having stored therein a set of risk types based on an induced taxonomy of risk types previously derived at least in part upon operation of a machine learning module, an input adapted to receive a set of source data, the set of source data being in electronic form and representing textual content comprising potential risk phrases, a entity-risk relation classifier adapted to identify and extract entity-risk relations from the set of source data, a risk tagger adapted to identify in the set of source data a set of risk candidates (ri) based on the set of risk types, a entity tagger adapted to identify mentions of entity names (ci) in the set of source data, and a risk register aggregator adapted to generate a first risk register based on the set of tuples associated with a first entity.
    Type: Application
    Filed: June 13, 2016
    Publication date: December 22, 2016
    Applicant: Thomson Reuters Global Resources
    Inventors: Jochen L. Leidner, Tim Nugent, Armineh Nourbakhsh, Sameena Shah
  • Publication number: 20160092793
    Abstract: Systems and methods for utilizing filters to reduce an incoming stream of textual messages to a smaller subset of potentially relevant textual messages, and using trained machine learning models to analyze and classify the content of such textual messages. Analyzed messages that belong to a relevant class as determined by the machine learning model are stored in a database, giving users the ability to determine and analyze trends from the subset of messages, such as adverse side effects caused by pharmaceuticals or the efficacy of pharmaceuticals. Relationships between the side effects caused by different pharmaceuticals can be used to predict potential candidates for drug repositioning.
    Type: Application
    Filed: September 22, 2015
    Publication date: March 31, 2016
    Inventors: Andrew G. Garrow, Jochen L. Leidner, Vasileios Plachouras, Timothy C.O. Nugent
  • Publication number: 20150112877
    Abstract: Exemplary systems for processing a corpus of documents, such as legal contracts or agreements, are disclosed. The systems include a phrase discovery engine which derives statistics and phrase equivalence classes, groups of phrase equivalence classes, and uberphrases (clauses) bounded by phrases. These can be used to determine origins of phrases or clauses within given legal contract or to suggest alternative phrases and clauses.
    Type: Application
    Filed: July 21, 2014
    Publication date: April 23, 2015
    Inventors: Frank Schilder, Jochen L. Leidner
  • Patent number: 8788523
    Abstract: Exemplary systems for processing a corpus of documents, such as legal contracts or agreements, are disclosed. The systems include a phrase discovery engine which derives statistics and phrase equivalence classes, groups of phrase equivalence classes, and uberphrases (clauses) bounded by phrases. These can be used to determine origins of phrases or clauses within given legal contract or to suggest alternative phrases and clauses.
    Type: Grant
    Filed: September 3, 2009
    Date of Patent: July 22, 2014
    Assignee: Thomson Reuters Global Resources
    Inventors: Kingsley Martin, Trace Liggett, Gary Berosik, Thomas Zielund, Dietmar Dorr, Jochen L. Leidner
  • Publication number: 20120221485
    Abstract: A computer implemented method for mining risks includes providing a set of risk-indicating patterns on a computing device; querying a corpus using the computing device to identify a set of potential risks by using a risk-identification-algorithm based, at least in part, on the set of risk-indicating patterns associated with the corpus; comparing the set of potential risks with the risk-indicating patterns to obtain a set of prerequisite risks; generating a signal representative of the set of prerequisite risks; storing the signal representative of the set of prerequisite risks in an electronic memory; and aggregating potential risks linked to an entity to an entity risk profile (ERP). A computing device or system for mining risks includes an electronic memory; and a risk-identification-algorithm based, at least in part, on the set of risk-indicating patterns associated with a corpus stored in the electronic memory.
    Type: Application
    Filed: March 16, 2012
    Publication date: August 30, 2012
    Inventors: Jochen L. Leidner, Frank Schilder
  • Publication number: 20120221486
    Abstract: A computer implemented method for mining risks includes providing a set of risk-indicating patterns on a computing device; querying a corpus using the computing device to identify a set of potential risks by using a risk-identification-algorithm based, at least in part, on the set of risk-indicating patterns associated with the corpus; comparing the set of potential risks with the risk-indicating patterns to obtain a set of prerequisite risks; generating a signal representative of the set of prerequisite risks; storing the signal representative of the set of prerequisite risks in an electronic memory; aggregating potential risks linked to an entity to an entity risk profile (ERP); and predicting a movement in a security associated with an entity.
    Type: Application
    Filed: March 16, 2012
    Publication date: August 30, 2012
    Inventors: Jochen L. Leidner, Frank Schilder
  • Publication number: 20110055206
    Abstract: Exemplary systems for processing a corpus of documents, such as legal contracts or agreements, are disclosed. The systems include a phrase discovery engine which derives statistics and phrase equivalence classes, groups of phrase equivalence classes, and uberphrases (clauses) bounded by phrases. These can be used to determine origins of phrases or clauses within given legal contract or to suggest alternative phrases and clauses.
    Type: Application
    Filed: September 3, 2009
    Publication date: March 3, 2011
    Applicant: West Services, Inc.
    Inventors: Kingsley Martin, Trace Liggett, Gary Berosik, Thomas Zielund, Dietmar Dorr, Jochen L. Leidner