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公开(公告)号：US11848027B2
公开(公告)日：2023-12-19
申请号：US17306004
申请日：2021-05-03
Applicant: SAP SE
Inventor： Kavitha Krishnan , Nicholas John Nicoloudis , Luxi Li , Pai-Hung Chen , Anton Kroger
CPC classification number: G10L25/30 , G06N3/04 , G06N3/08 , G10L19/0212 , G10L25/87
Abstract: In some example embodiments, there may be provided a method that includes receiving a machine learning model provided by a central server configured to provide federated learning; receiving first audio data obtained from at least one audio sensor monitoring at least one machine located at the first edge node; training, based on the first audio data, the machine learning model; providing parameter information to the central server in order to enable the federated learning among a plurality of edge nodes; receiving an aggregate machine learning model provided by the central server; detecting an anomalous state of the at least one machine. Related systems, methods, and articles of manufacture are also described.
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公开(公告)号：US20230147688A1
公开(公告)日：2023-05-11
申请号：US17521707
申请日：2021-11-08
Applicant: SAP SE
Inventor： Debashis Banerjee , Prateek Agarwal , Kavitha Krishnan
IPC: G06F12/0837 , G06F12/0877
CPC classification number: G06F12/0837 , G06F12/0877
Abstract: Some embodiments provide a program that receives a first set of data and a first greenhouse gas emission value. The program stores, in a cache, the first set of data and the first greenhouse gas emission value. The program receives a second set of data and a second greenhouse gas emission value. The program stores, in the cache, the second set of data and the second greenhouse gas emission value. The program receives a third set of data and a third greenhouse gas emission value. The program determines one of the first and second sets of data to remove from the cache based on the first and second greenhouse gas emission values. The program replaces, in the cache, one of the first and second sets of data and the corresponding first or second greenhouse gas emission value with the third set of data and the third greenhouse gas emission value.
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公开(公告)号：US11263551B2
公开(公告)日：2022-03-01
申请号：US16184651
申请日：2018-11-08
Applicant: SAP SE
Abstract: A method for machine-learning based process flow recommendation is provided. The method may include training a machine-learning model by at least processing training data with the machine-learning model. The training data may include a matrix representing one or more existing process flows by at least indicating actions that are performed on a document object to generate a subsequent document object. An indication that a first document object is created as part of a process flow may be received. In response to the indication, the trained machine-learning model may be applied to generate a recommendation to perform, as part of the process flow, an action to generate a second document object. Related systems and articles of manufacture, including computer program products, are also provided.
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公开(公告)号：US20240296460A1
公开(公告)日：2024-09-05
申请号：US18117234
申请日：2023-03-03
Applicant: SAP SE
Inventor： Gopi Kishan , Kavitha Krishnan , Rohit Jalagadugula , Sai Hareesh Anamandra , Akash Srivastava
IPC: G06Q30/018 , G06Q10/0875
CPC classification number: G06Q30/018 , G06Q10/0875
Abstract: A computer-implemented method can instantiate a net graph based on one or more existing bills of materials for one or more known entities. The net graph includes a plurality of interconnected nodes representing different objects included in the one or more known entities, and the one or more existing bill of materials define relationship between the objects. The method can determine carbon footprint values of the objects represented by the nodes, collect vectors of object features and carbon footprint values corresponding to selected nodes in the net graph, train a machine learning model using the collected vectors of object features and the carbon footprint values corresponding to the selected nodes, receiving a request associated with a target entity different from the one or more known entities, and responsive to the request, generate an estimated carbon footprint value for the target entity based on the machine learning model.
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公开(公告)号：US12019600B1
公开(公告)日：2024-06-25
申请号：US18125089
申请日：2023-03-22
Applicant: SAP SE
Inventor： Sai Hareesh Anamandra , Rohit Jalagadugula , Gopi Kishan , Akash Srivastava , Kavitha Krishnan , Jayanthi Subramanian , Diwakar Maurya
IPC: G06F16/24 , G06F16/22 , G06F16/2457
CPC classification number: G06F16/22 , G06F16/24575
Abstract: Technologies and solutions are provided for improving process efficiency/identifying efficient paths of process steps. A target outcome can be identified, which can be a particular status, such as a stage (or status/step) in a process, or a target outcome can be an identification of particular process statuses that can be reached, such as given a particular set of constraints. Proceeding between process steps involves the use of resources, where a process step can be reached, or having an increased chance of being reached, when the resources have been obtained. Various paths can exist for obtaining a resource, where some paths can be more efficient than others. Based on resource paths and paths between steps of a process, one or more paths can be suggested for reaching the target outcome, including providing information about the process step paths or the resources paths for reaching the target outcome.
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Patent Agency Ranking
公开(公告)号：US11966336B2
公开(公告)日：2024-04-23
申请号：US17521707
申请日：2021-11-08
Applicant: SAP SE
Inventor： Debashis Banerjee , Prateek Agarwal , Kavitha Krishnan
IPC: G06F12/0837 , G06F12/0877
CPC classification number: G06F12/0837 , G06F12/0877
Abstract: Some embodiments provide a program that receives a first set of data and a first greenhouse gas emission value. The program stores, in a cache, the first set of data and the first greenhouse gas emission value. The program receives a second set of data and a second greenhouse gas emission value. The program stores, in the cache, the second set of data and the second greenhouse gas emission value. The program receives a third set of data and a third greenhouse gas emission value. The program determines one of the first and second sets of data to remove from the cache based on the first and second greenhouse gas emission values. The program replaces, in the cache, one of the first and second sets of data and the corresponding first or second greenhouse gas emission value with the third set of data and the third greenhouse gas emission value.
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公开(公告)号：US20240078495A1
公开(公告)日：2024-03-07
申请号：US17897664
申请日：2022-08-29
Applicant: SAP SE
Inventor： Sai Hareesh Anamandra , Gopi Kishan , Rohit Jalagadugula , Akash Srivastava , Kavitha Krishnan , Vinay George Roy
CPC classification number: G06Q10/06398 , G06Q10/06395 , G06Q10/103
Abstract: Systems, methods, and computer media for determining compatible users through machine learning are provided herein. Previous interactions between some users in a group can be used to determine a first set of user-to-user compatibility scores. Both the first set of compatibility scores and attributes for the users in the group can be provided as inputs to a machine learning model that can be used to determine a second set of user-to-user compatibility scores for user pairs who do not have an interaction history. Along with input constraints, the first and second sets of user-to-user compatibility scores can be used to select compatible user groups.
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公开(公告)号：US11567775B1
公开(公告)日：2023-01-31
申请号：US17510100
申请日：2021-10-25
Applicant: SAP SE
Inventor： Debashis Banerjee , Paresh Rathod , Kavitha Krishnan , Prateek Agarwal , Hemanth Basrur
Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program observes a parameter associated with a computing system. Upon receiving a change associated with the parameter, the program further determines a routine definition from a set of routine definitions associated with the parameter. Each routine definition in the set of routine definitions specifies a set of instructions associated with a particular parameter associated with the computing system. The program also executes the set of instructions specified in the determined routine definition.
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公开(公告)号：US20220004917A1
公开(公告)日：2022-01-06
申请号：US16921449
申请日：2020-07-06
Applicant: SAP SE
Inventor： Kavitha Krishnan , Ashok Veilumuthu , Baber Farooq
Abstract: In an example embodiment, a recommendation engine provides recommendations as to how decision-making units (DMUs) can improve efficiency, or savings can utilize machine learning algorithms and data envelopment analysis (DEA). DEA is a linear programming methodology, and is used in the example embodiment to identify one or more key performance indices (KPIs) that are most important to a DMU.
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公开(公告)号：US12159174B2
公开(公告)日：2024-12-03
申请号：US17948652
申请日：2022-09-20
Applicant: SAP SE
Inventor： Sai Hareesh Anamandra , Gopi Kishan , Kavitha Krishnan , Rohit Jalagadugula , Akash Srivastava
Abstract: A method includes receiving a message query from an entity identifier participating in a social network. The message query specifies one or more entities, one or more requirements, and one or more constraints. A set of message query parameters is generated based on the message query. A set of queries for a semantic graph of the social network is generated based on the set of message query parameters. The set of queries is applied to the semantic graph to obtain a set of query results. A message context of the entity identifier is determined based on the set of query results and the set of message query parameters. A set of messages from a message repository is determined based on the message context. The set of messages can be presented on a client computer associated with the entity identifier.
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