Patents by Inventor John H. Bauer

John H. Bauer 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: 10643140
    Abstract: A method includes performing contextual association of entities using multi-source data. For each context the method performs co-clustering to identify distinct expert-skill associations; constructing single-entity unipartite graph representations and performing a random walk within each single-entity unipartite graph; for each single-entity unipartite graph, obtaining steady state distributions using the random walks to obtain clusters of experts and skills; performing a weighted two-way random walk across entity graphs (graph edges), giving preference to traversal within members of the same co-cluster; and performing link prediction for each context by dynamically adding edges, and obtaining overall skills predictions, analyses and inferences by merging the contexts and weighting the links of each context.
    Type: Grant
    Filed: May 1, 2014
    Date of Patent: May 5, 2020
    Assignee: International Business Machines Corporation
    Inventors: John H. Bauer, Dongping Fang, Aleksandra Mojsilovic, Karthikeyan N. Ramamurthy, Kush R. Varshney, Jun Wang
  • Publication number: 20180121823
    Abstract: A method includes performing contextual association of entities using multi-source data. For each context the method performs co-clustering to identify distinct expert-skill associations; constructing single-entity unipartite graph representations and performing a random walk within each single-entity unipartite graph; for each single-entity unipartite graph, obtaining steady state distributions using the random walks to obtain clusters of experts and skills; performing a weighted two-way random walk across entity graphs (graph edges), giving preference to traversal within members of the same co-cluster; and performing link prediction for each context by dynamically adding edges, and obtaining overall skills predictions, analyses and inferences by merging the contexts and weighting the links of each context.
    Type: Application
    Filed: December 27, 2017
    Publication date: May 3, 2018
    Inventors: John H. Bauer, Dongping Fang, Aleksandra Mojsilovic, Karthikeyan N. Ramamurthy, Kush R. Varshney, Jun Wang
  • Publication number: 20150317376
    Abstract: A method includes performing contextual association of entities using multi-source data. For each context the method performs co-clustering to identify distinct expert-skill associations; constructing single-entity unipartite graph representations and performing a random walk within each single-entity unipartite graph; for each single-entity unipartite graph, obtaining steady state distributions using the random walks to obtain clusters of experts and skills; performing a weighted two-way random walk across entity graphs (graph edges), giving preference to traversal within members of the same co-cluster; and performing link prediction for each context by dynamically adding edges, and obtaining overall skills predictions, analyses and inferences by merging the contexts and weighting the links of each context.
    Type: Application
    Filed: May 1, 2014
    Publication date: November 5, 2015
    Applicant: International Business Machines Corporation
    Inventors: John H. Bauer, Dongping Fang, Aleksandra Mojsilovic, Karthikeyan N. Ramamurthy, Kush R. Varshney, Jun Wang