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公开(公告)号：US11681969B2
公开(公告)日：2023-06-20
申请号：US16921449
申请日：2020-07-06
Applicant: SAP SE
Inventor： Kavitha Krishnan , Ashok Veilumuthu , Baber Farooq
IPC: G06Q30/00 , G06Q10/0639 , G06N20/00 , G06F18/214 , G06F18/2413
CPC classification number: G06Q10/06393 , G06F18/214 , G06F18/24147 , G06N20/00
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：US20230096720A1
公开(公告)日：2023-03-30
申请号：US17486126
申请日：2021-09-27
Applicant: SAP SE
Inventor： Martin Wezowski , Hans-Martin Will , Rohit Jalagadugula , Kavitha Krishnan , Sai Hareesh Anamandra , Vinay George Roy , Parthasarathy Menon , Alexander Schaefer
IPC: G06Q10/06
Abstract: A method may include collecting data from a variety of data sources associated with a user. The data sources may include personal data sources, corporate data sources, and public data source. The data collected from the variety of data sources may be enriched through categorization and aggregation. For example, browser history may be categorized based on types of website and aggregated to reflect the quantity of interactions with each category of website. A multi-dimensional digital profile may be generated based on the enriched data. For instance, the digital profile may include a social, emotional, spiritual, environmental, occupational, intellectual, and physical dimension. One or more recommendation corresponding to one or more of a burnout prediction, wellness recommendation, learning plan, skill gap, and personality type may be generated based on the digital profile. Related systems and computer program products are also provided.
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公开(公告)号：US20220351744A1
公开(公告)日：2022-11-03
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
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：US20210174195A1
公开(公告)日：2021-06-10
申请号：US16707592
申请日：2019-12-09
Applicant: SAP SE
Abstract: A method may include applying, to various factors contributing to a sentiment that an end user exhibits towards an enterprise software application, a first machine learning model trained to determine, based on the factors, a sentiment index indicating the sentiment that the end user exhibits towards the enterprise software application. In response to the sentiment index exceeding a threshold value, a second machine learning model may be applied to identify remedial actions for addressing one or more of the factors contributing to the sentiment of the end user. A user interface may be generated to display, at a client device, a recommendation including the remedial actions. The remedial actions may be prioritized based on how much each corresponding factor contribute to the sentiment of the end user. Related systems and articles of manufacture are also provided.
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公开(公告)号：US20240095105A1
公开(公告)日：2024-03-21
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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Patent Agency Ranking
公开(公告)号：US11853950B2
公开(公告)日：2023-12-26
申请号：US17486126
申请日：2021-09-27
Applicant: SAP SE
Inventor： Martin Wezowski , Hans-Martin Will , Rohit Jalagadugula , Kavitha Krishnan , Sai Hareesh Anamandra , Vinay George Roy , Parthasarathy Menon , Alexander Schaefer
IPC: G06Q10/0639 , G06Q10/067 , G06Q10/0633 , H04L67/50
CPC classification number: G06Q10/06398 , G06Q10/067 , G06Q10/0633 , H04L67/535
Abstract: A method may include collecting data from a variety of data sources associated with a user. The data sources may include personal data sources, corporate data sources, and public data source. The data collected from the variety of data sources may be enriched through categorization and aggregation. For example, browser history may be categorized based on types of website and aggregated to reflect the quantity of interactions with each category of website. A multi-dimensional digital profile may be generated based on the enriched data. For instance, the digital profile may include a social, emotional, spiritual, environmental, occupational, intellectual, and physical dimension. One or more recommendation corresponding to one or more of a burnout prediction, wellness recommendation, learning plan, skill gap, and personality type may be generated based on the digital profile. Related systems and computer program products are also provided.
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公开(公告)号：US20230131099A1
公开(公告)日：2023-04-27
申请号：US17508699
申请日：2021-10-22
Applicant: SAP SE
Inventor： Sai Hareesh Anamandra , Kavitha Krishnan , Rohit Jalagadugula , Parthasarathy Menon , Aditi D'Souza , Shrusti Mohanty , Lingyun Bu , Vinay George Roy
IPC: G06Q10/06 , G06N5/04 , G16H50/70 , G16H50/20 , G06Q10/10 , A61B5/11 , A61B5/0205 , A61B5/024 , A61B5/00
Abstract: A method may include training one or more machine learning models to predict a decline in employee performance. The machine learning models may be trained in a federated manner to avoid the exchange of personal data. The trained machine learning models may be applied to data associated with an employee that corresponds to one or more leading indicators of employee burnout. In response to the trained machine learning models predicting a decline in the performance of the employee, the root causes of the predicted decline in the performance of the employee may be identified by applying an explainability algorithm such as Shapley Additive Explanations (SHAP). A report including a corrective action for the predicted decline in employee performance may be generated based on the root causes. Related systems and computer program products are also provided.
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公开(公告)号：US20200349592A1
公开(公告)日：2020-11-05
申请号：US16403021
申请日：2019-05-03
Applicant: SAP SE
Abstract: Briefly, embodiments of a system, method, and article for processing a set of indicators from an indicator repository are disclosed. An indicator anomaly may be detected within one of more of the individual indicators of the set of indicators based, at least in part, on a threshold increase in publication of the one or more of the individual indicators within a particular time period. A determination may be made as to whether one or more particular indicators of the set of indicators had a causal impact on a transactions anomaly within the particular time period. A notification may be generated to identify the one or more particular indicators at least particularly in response to the determining that the one or more particular indicators of the set of indicators had a causal impact on a transactions anomaly.
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公开(公告)号：US20250094255A1
公开(公告)日：2025-03-20
申请号：US18965886
申请日：2024-12-02
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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公开(公告)号：US20240104153A1
公开(公告)日：2024-03-28
申请号：US17951320
申请日：2022-09-23
Applicant: SAP SE
Inventor： Gopi Kishan , Rohit Jalagadugula , Kavitha Krishnan , Sai Hareesh Anamandra , Akash Srivastava
IPC: G06F16/9536 , G06F16/9532 , G06F16/954
CPC classification number: G06F16/9536 , G06F16/9532 , G06F16/954 , G06F16/9538
Abstract: A method includes receiving, at a search toolbar, a search query from a machine in a network. The machine has an associated machine profile for participating in the network as an entity. The machine profile includes a machine identifier and machine metadata. A query type is determined from the search query. A search context for the machine is determined using a semantic graph of the network. From a set of services for the network, one or more relevant services to respond to the search query are identified based on the query type and the search context. The search query is applied to the one or more relevant services to obtain a set of responses. A set of relevant results for the search query is determined from the set of responses. The set of relevant results is transmitted to the machine.
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