Service token handling
    2.
    发明授权

    公开(公告)号:US10097562B2

    公开(公告)日:2018-10-09

    申请号:US15148165

    申请日:2016-05-06

    Applicant: SAP SE

    Abstract: A system includes reception, at a server and in a first browser session, of a request from a client for a token to access a first software service, determination of a token stored in a server memory of the server and associated with the first service and the client, determination, at the server, of whether a validity period of the token is within a predetermined period of expiration, and, if it is determined that the validity period of the token is within a predetermined period of expiration, transmission of a request for a new token to access the first software service from a token provider associated with the first service, reception of the new token from the token provider, and provision of the new token to the client in the first browser session.

    SERVICE TOKEN HANDLING
    3.
    发明申请

    公开(公告)号:US20170324749A1

    公开(公告)日:2017-11-09

    申请号:US15148165

    申请日:2016-05-06

    Applicant: SAP SE

    Abstract: A system includes reception, at a server and in a first browser session, of a request from a client for a token to access a first software service, determination of a token stored in a server memory of the server and associated with the first service and the client, determination, at the server, of whether a validity period of the token is within a predetermined period of expiration, and, if it is determined that the validity period of the token is within a predetermined period of expiration, transmission of a request for a new token to access the first software service from a token provider associated with the first service, reception of the new token from the token provider, and provision of the new token to the client in the first browser session.

    RULES DETERMINATION VIA KNOWLEDGE GRAPH
    4.
    发明公开

    公开(公告)号:US20240152781A1

    公开(公告)日:2024-05-09

    申请号:US18102798

    申请日:2023-01-30

    Applicant: SAP SE

    CPC classification number: G06N5/04

    Abstract: The example embodiments are directed to a host system that can convert human-readable rules (e.g., statutes, regulations, laws, etc.) into a semantic model. The host system can then apply the semantic model to a set of circumstances to determine whether and how the rule applies to the circumstances. In one example, the method may include storing a knowledge graph with a semantic model of a rule embodied therein with nodes representing entities within the rule, edges between the nodes representing relationships between the entities, and identifiers of an input data set used by the rule, receiving input data corresponding to the rule, generating a determination from the rule via execution of the semantic model embodied within the knowledge graph on the received input data, and displaying a notification of the determination via a user interface.

    Dynamic form with machine learning

    公开(公告)号:US11580440B2

    公开(公告)日:2023-02-14

    申请号:US15368007

    申请日:2016-12-02

    Applicant: SAP SE

    Abstract: Methods, computer-readable media and systems are disclosed for building, deploying, operating, and maintaining an intelligent dynamic form in which a trained machine learning (ML) model is embedded. A universe of questions is associated with a plurality of output classifiers, which could represent eligibilities for respective benefits. The questions are partitioned into blocks. Each block can be associated with one or more of the classifiers, and each classifier can have a dependency on one or more blocks. An ML model is trained to make inferences from varied combinations of responses to questions and pre-existing data, and determine probabilities or predictions of values of the output classifiers. Based on outputs of the trained model, blocks of questions can be selectively rendered. The trained model is packaged with the question blocks and other components suitably for offline deployment. Uploading collected responses and maintenance of the dynamic form are also disclosed.

    Lock mode determination service
    6.
    发明授权

    公开(公告)号:US10474664B2

    公开(公告)日:2019-11-12

    申请号:US15454470

    申请日:2017-03-09

    Applicant: SAP SE

    Abstract: Methods and systems are disclosed for flexibly managing lock modes in a data-sharing environment, including optimistic and pessimistic lock modes. A lock mode determination service receives a request from an application instance for a lock mode with which to access specified data objects. The service can determine and provide a suitable lock mode based on a context of the application, and optionally other parameters, by evaluating a checklist of criteria sorted in precedential order. Criteria can include geo-boundaries, platform, role, and others. The requesting application instance uses the determined lock mode to access the data, with optional assistance of a lock service. The lock mode determination service can support one or more applications having one or more instances each, and can also support multiple disjoint data-sharing environments. Suitable environments include cloud, datacenter, mobile, client-server, and SAAS.

    Adaptive data retrieval with runtime authorization

    公开(公告)号:US11567930B2

    公开(公告)日:2023-01-31

    申请号:US15497106

    申请日:2017-04-25

    Applicant: SAP SE

    Abstract: Methods and systems are disclosed for data retrieval, from databases to clients, in an environment requiring runtime authorization. In response to a request for T data records, a learning module provides a prediction R of a suitable number of data records to retrieve from a database. Following retrieval of R records or record identifiers, authorization is sought from an authorization service, resulting in A of the records being authorized. The A authorized records are returned to the requesting client, and, if more records are needed, T is decremented and the cycle is repeated. A performance notification is provided to the learning module for training, with respect to providing values of prediction R. The performance notification can be based on a measure of authorization service performance, the number A of authorized records, latency, communication or resource costs, a measure of resource congestion, or other parameters. Variants are disclosed.

    LOCK MODE DETERMINATION SERVICE
    9.
    发明申请

    公开(公告)号:US20180260429A1

    公开(公告)日:2018-09-13

    申请号:US15454470

    申请日:2017-03-09

    Applicant: SAP SE

    CPC classification number: G06F16/2343 G06F9/526

    Abstract: Methods and systems are disclosed for flexibly managing lock modes in a data-sharing environment, including optimistic and pessimistic lock modes. A lock mode determination service receives a request from an application instance for a lock mode with which to access specified data objects. The service can determine and provide a suitable lock mode based on a context of the application, and optionally other parameters, by evaluating a checklist of criteria sorted in precedential order. Criteria can include geo-boundaries, platform, role, and others. The requesting application instance uses the determined lock mode to access the data, with optional assistance of a lock service. The lock mode determination service can support one or more applications having one or more instances each, and can also support multiple disjoint data-sharing environments. Suitable environments include cloud, datacenter, mobile, client-server, and SAAS.

    PROCESS EXECUTION USING RULES FRAMEWORK FLEXIBLY INCORPORATING PREDICTIVE MODELING

    公开(公告)号:US20180114135A1

    公开(公告)日:2018-04-26

    申请号:US15333745

    申请日:2016-10-25

    Applicant: SAP SE

    CPC classification number: G06Q10/0637 G06N5/025

    Abstract: A specification of the process model is received. The process model includes a plurality of process components. A relationship between a first process component and another process component of the plurality of process components is determined using a predictive model. A process rule for the first process component is determined. The process rule specified a second process component to be executed. The process rule includes the relationship determined using the predictive model or a heuristic rule. The second process component is executed according to the process rule.

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