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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：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：US20190392498A1
公开(公告)日：2019-12-26
申请号：US16017399
申请日：2018-06-25
Applicant: SAP SE
Inventor： Mridul Sarkar , Kumar Nitesh
Abstract: A method and system including receiving a first set of document files comprising textual terms relating to a plurality of first users; receiving a second set of document files relating to a second user from one or more data sources, the second set of document files including a plurality of textual terms associated with the second user from a combination of documents; determining whether the second set of document files is similar to one or more documents in the first set of document files based on a collaborative filtering process of the textual terms derived from the second set of document files and the first set of document files; generating an indicator that indicates a level of similarity between the second set of document files and the one or more documents in the first set of document files; and outputting a user interface displaying the generated indicator.
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公开(公告)号：US20200151615A1
公开(公告)日：2020-05-14
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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