公开(公告)号：GB2584063A

公开(公告)日：2020-11-18

申请号：GB202014014

申请日：2019-02-12

Applicant: IBM

Inventor： STEFAN RAVIZZA ,  ANDREA GIOVANNINI ,  TIM UWE SCHEIDELER ,  FREDERIK FRANK FLÖTHER ,  FLORIAN GRAF ,  ERIK RUEGER

IPC: G06F21/60 ,  G06F21/62

Abstract: A computer-implemented method, system, and computer program product for dynamic access control to a node in a knowledge graph includes: structuring nodes of a knowledge graph into a plurality of hierarchically organized graph layers; assigning, to a user, an access right to a node of the knowledge graph, the access right to the node selected from a plurality of access rights; and changing the access right to the node dynamically, the changing based on at least one of a structure of the knowledge graph, an access history of the user to the node, and a parameter of the user indicative of a condition outside the knowledge graph.

公开(公告)号：GB2578981B

公开(公告)日：2021-04-21

申请号：GB202000528

申请日：2018-07-18

Applicant: IBM

Inventor： STEFAN RAVIZZA ,  TIM UWE SCHEIDELER ,  ERIK RUEGER ,  THORSTEN MUEHGE

IPC: G06F16/185

Abstract: A cognitive hierarchical storage-management system receives feedback describing users' satisfaction with the way that one or more prior data-access requests were serviced. The system uses this feedback to associate each previously requested data element's metadata and storage tier with a level of user satisfaction, and to optimize user satisfaction when the system is trained. As feedback continues to be received, the system uses machine-learning methods to identify how closely specific metadata patterns correlate with certain levels of user satisfaction and with certain storage tiers. The system then uses the resulting associations when determining whether to migrate data associated with a particular metadata pattern to a different tier. Data elements may be migrated between different tiers when two metadata sets share metadata values. A user's degree of satisfaction may be encoded as a metadata element that may be used to train a neural network of a machine-learning module. If detecting that two metadata sets share metadata values, the system determines whether to migrate data elements to different tiers.

公开(公告)号：GB2597406A

公开(公告)日：2022-01-26

申请号：GB202115858

申请日：2020-03-18

Applicant: IBM

Inventor： GEORGIOS CHALOULOS ,  FREDERIK FLOETHER ,  FLORIAN GRAF ,  PATRICK LUSTENBERGER ,  STEFAN RAVIZZA ,  ERIC SLOTTKE

IPC: G06N20/00

Abstract: A computer-implemented method for improving fairness in a supervised machine-learning model may be provided. The method comprises linking the supervised machine-learning model to a reinforcement learning meta model, selecting a list of hyper-parameters and parameters of the supervised machine-learning model, and controlling at least one aspect of the supervised machine-learning model by adjusting hyper-parameters values and parameter values of the list of hyper-parameters and parameters of the supervised machine-learning model by a reinforcement learning engine relating to the reinforcement learning meta model by calculating a reward function based on multiple conflicting objective functions. The method further comprises repeating iteratively the steps of selecting and controlling for improving a fairness value of the supervised machine-learning model.

公开(公告)号：GB2592335A

公开(公告)日：2021-08-25

申请号：GB202108987

申请日：2019-11-22

Applicant: IBM

Inventor： TIM SCHEIDELER ,  ERIK RUEGER ,  STEFAN RAVIZZA ,  FREDERIK FLOETHER

IPC: G06F16/35 ,  G06F16/901 ,  G06F16/906

Abstract: A method for partitioning a knowledge graph is provided. The method analyzes past searches and determines an access frequency of a plurality of edges. The method marks, as intermediate cluster cores, edges having the highest access frequencies, sorts the marked 5intermediate cluster cores according to their access frequencies, and selects a first cluster core having the highest access frequency. The method assigns first edges in a first radiusaround the first cluster core to build the first cluster. The method selects a second cluster core having the highest access frequency apart from edges of the first cluster, and assignssecond edges in a second radius around second cluster core to build the second cluster. The 0method partitions the knowledge graph into a first sub-knowledge-graph comprising the first cluster and a second sub-knowledge-graph comprising the second cluster.

公开(公告)号：GB2584063B

公开(公告)日：2021-04-21

申请号：GB202014014

申请日：2019-02-12

Applicant: IBM

Inventor： STEFAN RAVIZZA ,  ANDREA GIOVANNINI ,  TIM UWE SCHEIDELER ,  FREDERIK FRANK FLÖTHER ,  FLORIAN GRAF ,  ERIK RUEGER

IPC: G06F21/60 ,  G06F21/62

Abstract: A computer-implemented method, system, and computer program product for dynamic access control to a node in a knowledge graph includes: structuring nodes of a knowledge graph into a plurality of hierarchically organized graph layers; assigning, to one or more users, an access right to a first node of the knowledge graph, the access right to the node selected from a plurality of access rights, where different types of users have different access rights; and assigning, to at least one user from the one or more users, an additional access right to a second node of the knowledge graph.

公开(公告)号：GB2581761A

公开(公告)日：2020-08-26

申请号：GB202009501

申请日：2018-11-23

Applicant: IBM

Inventor： TIM UWE SCHEIDELER ,  STEFAN RAVIZZA ,  ANDREA GIOVANNINI ,  AVDYL HAXHAJ ,  SIMON STREIT ,  FLORIAN GRAF

IPC: G06N5/02 ,  G06N20/00

Abstract: A computer program product, system, and method for building a knowledge graph may include receiving a plurality of new nodes, receiving a base knowledge graph having existing nodes selectively connected by existing edges, and superimposing the new nodes onto selected ones of the existing nodes of the base knowledge graph. The method may further include connecting the new nodes by creating a new edge with a new weight between at least two of the new nodes if corresponding existing nodes in the underlying base knowledge graph have a connection via zero or a predetermined maximum number of existing edges, wherein the new weight is determined based on the existing weights of the existing edges of connections between the corresponding existing nodes, and detaching the new nodes with the new edges from the base knowledge graph.

公开(公告)号：GB2579006A

公开(公告)日：2020-06-03

申请号：GB202003665

申请日：2018-08-21

Applicant: IBM

Inventor： ANDREA GIOVANNINI ,  STEFAN RAVIZZA ,  TIM UWE SCHEIDELER ,  FLORIAN GRAF

IPC: G06N5/04 ,  G06F16/2458

Abstract: A method includes receiving a first query by a computing device and assigning the first query to a plurality of cognitive engines, wherein each of the plurality of cognitive engines include different characteristics for processing data. The method also includes, responsive to receiving a response from each of the plurality of cognitive engines for the first query, comparing the received responses from the plurality of cognitive engines. The method also included responsive to determining a difference between a first response from a first cognitive engine and a second response from a second cognitive engine is above a predetermined threshold value, performing a response mediation process until the difference is below the predetermined threshold value.The method also includes selecting a first final response from the received responses for the first query and the second query and displaying the first final response to a user.

公开(公告)号：GB2578981A

公开(公告)日：2020-06-03

申请号：GB202000528

申请日：2018-07-18

Applicant: IBM

Inventor： STEFAN RAVIZZA ,  TIM UWE SCHEIDELER ,  ERIK RUEGER ,  THORSTEN MUEHGE

IPC: G06F16/00

Abstract: A cognitive hierarchical storage-management system receives feedback describing users' satisfaction with the way that prior data-access requests have been serviced. The system uses this feedback to associate each previously requested data element's metadata and storage tier with a level of user satisfaction. As feedback continues to be received, the system uses machine-learning methods to identify how closely specific metadata patterns correlate with certain levels of user satisfaction and with certain storage tiers. The system then uses these associations when determining whether it should migrate data associated with a particular metadata pattern to a different tier.