Patents by Inventor Joseph F. Murray
Joseph F. Murray 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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Publication number: 20220358516Abstract: An automated system for detecting risky entity behavior using an efficient frequent behavior-sorted list is disclosed. From these lists, fingerprints and distance measures can be constructed to enable comparison to known risky entities. The lists also facilitate efficient linking of entities to each other, such that risk information propagates through entity associations. These behavior sorted lists, in combination with other profiling techniques, which efficiently summarize information about the entity within a data store, can be used to create threat scores. These threat scores may be applied within the context of anti-money laundering (AML) and retail banking fraud detection systems. A particular instantiation of these scores elaborated here is the AML Threat Score, which is trained to identify behavior for a banking customer that is suspicious and indicates high likelihood of money laundering activity.Type: ApplicationFiled: July 1, 2022Publication date: November 10, 2022Inventors: Scott Michael Zoldi, Joseph F. Murray
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Patent number: 11423414Abstract: An automated system for detecting risky entity behavior using an efficient frequent behavior-sorted list is disclosed. From these lists, fingerprints and distance measures can be constructed to enable comparison to known risky entities. The lists also facilitate efficient linking of entities to each other, such that risk information propagates through entity associations. These behavior sorted lists, in combination with other profiling techniques, which efficiently summarize information about the entity within a data store, can be used to create threat scores. These threat scores may be applied within the context of anti-money laundering (AML) and retail banking fraud detection systems. A particular instantiation of these scores elaborated here is the AML Threat Score, which is trained to identify behavior for a banking customer that is suspicious and indicates high likelihood of money laundering activity.Type: GrantFiled: March 18, 2016Date of Patent: August 23, 2022Assignee: FAIR ISAAC CORPORATIONInventors: Scott Michael Zoldi, Joseph F. Murray
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Patent number: 10896381Abstract: An automated way of learning archetypes which capture many aspects of entity behavior, and assigning entities to a mixture of archetypes, such that each entity is represented as a distribution across multiple archetypes. Given those representations in archetypes, anomalous behavior can be detected by finding misalignment with a plurality of entities archetype clustering within a hard segmentation. Extensions to sequence modeling are also discussed. Applications of this method include anti-money laundering (where the entities can be customers and accounts, as described extensively below), retail banking fraud detection, network security, and general anomaly detection.Type: GrantFiled: March 18, 2016Date of Patent: January 19, 2021Assignee: Fair Isaac CorporationInventors: Scott Michael Zoldi, Joseph F. Murray
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Patent number: 10367888Abstract: A system and method for rapid data investigation and data integrity analysis is disclosed. A data set is received by a server computer from one or more client computers connected with the server computer via a communications network, and the data set is stored in a distributed storage memory. One or more analytical processes are executed on the data set from the distributed storage memory to generate statistics based on each of the analytical processes, and the statistics are stored in a random access memory, the random access memory being accessible by one or more compute nodes, which generate a graphical representation of at least some statistics stored in the random access memory. The graphical representation of at least some statistics is then formatted for transmission to and display by the one or more client computers.Type: GrantFiled: September 20, 2017Date of Patent: July 30, 2019Assignee: FAIR ISAAC CORPORATIONInventors: Scott M. Zoldi, Joseph F. Murray, Jeffrey D. Carlson
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Publication number: 20180013829Abstract: A system and method for rapid data investigation and data integrity analysis is disclosed. A data set is received by a server computer from one or more client computers connected with the server computer via a communications network, and the data set is stored in a distributed storage memory. One or more analytical processes are executed on the data set from the distributed storage memory to generate statistics based on each of the analytical processes, and the statistics are stored in a random access memory, the random access memory being accessible by one or more compute nodes, which generate a graphical representation of at least some statistics stored in the random access memory. The graphical representation of at least some statistics is then formatted for transmission to and display by the one or more client computers.Type: ApplicationFiled: September 20, 2017Publication date: January 11, 2018Inventors: Scott M. Zoldi, Joseph F. Murray, Jeffrey D. Carlson
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Patent number: 9799098Abstract: Identifying objects in images is a difficult problem, particularly in cases an original image is noisy or has areas narrow in color or grayscale gradient. A technique employing a convolutional network has been identified to identify objects in such images in an automated and rapid manner. One example embodiment trains a convolutional network including multiple layers of filters. The filters are trained by learning and are arranged in successive layers and produce images having at least a same resolution as an original image. The filters are trained as a function of the original image or a desired image labeling; the image labels of objects identified in the original image are reported and may be used for segmentation. The technique can be applied to images of neural circuitry or electron microscopy, for example. The same technique can also be applied to correction of photographs or videos.Type: GrantFiled: April 24, 2008Date of Patent: October 24, 2017Assignees: Massachusetts Institute of Technology, Max-Planck-Gesellschaft Zur Forderung Der Wissenschaften E.V.Inventors: H. Sebastian Seung, Joseph F. Murray, Viren Jain, Srinivas C. Turaga, Moritz Helmstaedter, Winfried Denk
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Patent number: 9774681Abstract: A system and method for rapid data investigation and data integrity analysis is disclosed. A data set is received by a server computer from one or more client computers connected with the server computer via a communications network, and the data set is stored in a distributed storage memory. One or more analytical processes are executed on the data set from the distributed storage memory to generate statistics based on each of the analytical processes, and the statistics are stored in a random access memory, the random access memory being accessible by one or more compute nodes, which generate a graphical representation of at least some statistics stored in the random access memory. The graphical representation of at least some statistics is then formatted for transmission to and display by the one or more client computers.Type: GrantFiled: October 3, 2014Date of Patent: September 26, 2017Inventors: Scott M. Zoldi, Joseph F. Murray, Jeffrey D. Carlson
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Publication number: 20170270534Abstract: An automated system for detecting risky entity behavior using an efficient frequent behavior-sorted list is disclosed. From these lists, fingerprints and distance measures can be constructed to enable comparison to known risky entities. The lists also facilitate efficient linking of entities to each other, such that risk information propagates through entity associations. These behavior sorted lists, in combination with other profiling techniques, which efficiently summarize information about the entity within a data store, can be used to create threat scores. These threat scores may be applied within the context of anti-money laundering (AML) and retail banking fraud detection systems. A particular instantiation of these scores elaborated here is the AML Threat Score, which is trained to identify behavior for a banking customer that is suspicious and indicates high likelihood of money laundering activity.Type: ApplicationFiled: March 18, 2016Publication date: September 21, 2017Inventors: Scott Michael Zoldi, Joseph F. Murray
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Publication number: 20170270428Abstract: An automated way of learning archetypes which capture many aspects of entity behavior, and assigning entities to a mixture of archetypes, such that each entity is represented as a distribution across multiple archetypes. Given those representations in archetypes, anomalous behavior can be detected by finding misalignment with a plurality of entities archetype clustering within a hard segmentation. Extensions to sequence modeling are also discussed. Applications of this method include anti-money laundering (where the entities can be customers and accounts, as described extensively below), retail banking fraud detection, network security, and general anomaly detection.Type: ApplicationFiled: March 18, 2016Publication date: September 21, 2017Inventors: Scott Michael Zoldi, Joseph F. Murray
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Publication number: 20160100009Abstract: A system and method for rapid data investigation and data integrity analysis is disclosed. A data set is received by a server computer from one or more client computers connected with the server computer via a communications network, and the data set is stored in a distributed storage memory. One or more analytical processes are executed on the data set from the distributed storage memory to generate statistics based on each of the analytical processes, and the statistics are stored in a random access memory, the random access memory being accessible by one or more compute nodes, which generate a graphical representation of at least some statistics stored in the random access memory. The graphical representation of at least some statistics is then formatted for transmission to and display by the one or more client computers.Type: ApplicationFiled: October 3, 2014Publication date: April 7, 2016Inventors: Scott M. Zoldi, Joseph F. Murray, Jeffrey D. Carlson
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Publication number: 20130340507Abstract: A viscosity measuring instrument for measuring ceramic slurries, e.g. in a casting tank, with a probe having an elbow and presenting a transducer part in substantial alignment with a flow direction of the ceramic slurry relative to the active part and a barrier orthogonal to such relative movement direction is interposed in front of the transducer part by one or more stand-off rods to form a partial enclosure that moderates flow to the active part and provides a long term stable measuring capability.Type: ApplicationFiled: June 20, 2012Publication date: December 26, 2013Applicant: BROOKFIELD ENGINEERING LABORATORIES INC.Inventors: David A. Brookfield, Steven Cicchese, Joseph F. Murray
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Publication number: 20100183217Abstract: Identifying objects in images is a difficult problem, particularly in cases an original image is noisy or has areas narrow in color or grayscale gradient. A technique employing a convolutional network has been identified to identify objects in such images in an automated and rapid manner. One example embodiment trains a convolutional network including multiple layers of filters. The filters are trained by learning and are arranged in successive layers and produce images having at least a same resolution as an original image. The filters are trained as a function of the original image or a desired image labeling; the image labels of objects identified in the original image are reported and may be used for segmentation. The technique can be applied to images of neural circuitry or electron microscopy, for example. The same technique can also be applied to correction of photographs or videos.Type: ApplicationFiled: April 24, 2008Publication date: July 22, 2010Inventors: H. Sebastian Seung, Joseph F. Murray, Viren Jain, Srinivas C. Turaga, Moritz Helmstaedter, Winfried Denk