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    DYNAMIC HIERARCHY GENERATION BASED ON GRAPH DATA
    2.
    发明申请
    DYNAMIC HIERARCHY GENERATION BASED ON GRAPH DATA 审中-公开

    公开(公告)号：US20180018402A1

    公开(公告)日：2018-01-18

    申请号：US15207666

    申请日：2016-07-12

    Applicant: SAP SE

    Inventor： Hartmut Vogler ,  Torsten Heise ,  Kefeng Wang ,  Tarek Auel ,  Lukas Mairon ,  Maiko Mueller ,  Sudhir Rao ,  Michael Boettcher ,  Sven Hader

    IPC: G06F17/30

    CPC classification number: G06F16/9024 ,  G06F16/2246 ,  G06F16/282

    Abstract: Provided are systems and methods for generating a hierarchy. In one example, a method includes receiving a first data graph including a plurality of nodes and links connecting the plurality of nodes, receiving a second data graph including a second plurality of nodes and links connecting the second plurality of nodes, generating a hierarchy based on the first data graph and the second data graph, where the generated hierarchy includes a plurality of levels, nodes from the first data graph arranged on at least one level, nodes from the second data graph arranged on at least one other level, and links connecting the nodes from the first data graph and the nodes from the second data graph, and indicating a relationships between the first and second data items, and outputting the generated hierarchy for at least one of display and further processing.

    Intelligent outlier data detection
    4.
    发明授权
    Intelligent outlier data detection 有权

    公开(公告)号：US11354384B2

    公开(公告)日：2022-06-07

    申请号：US16711178

    申请日：2019-12-11

    Applicant: SAP SE

    Inventor： Kefeng Wang

    IPC: G06F17/18 ,  G06F11/32 ,  G06F16/903

    Abstract: Transaction data is received from a remote client computing device that includes user-generated entries in each of a plurality of fields. Thereafter, it can be determined, using an outlier detection algorithm, that values for one or more of the entries is an outlier. Data can then be provided (e.g., displayed in a visual display, loaded into memory, stored in physical persistence, transmitted to a remote computing system, etc.). The outlier algorithm can be based on a number of similar records g, a number of distinct values d(g) in the similar records, and a number of same values s in the similar records. Related apparatus, systems, techniques and articles are also described.

    Hierarchically Stored Data Processing
    5.
    发明申请
    Hierarchically Stored Data Processing 审中-公开

    公开(公告)号：US20180150478A1

    公开(公告)日：2018-05-31

    申请号：US15363326

    申请日：2016-11-29

    Applicant: SAP SE

    Inventor： Kefeng Wang

    IPC: G06F17/30

    CPC classification number: G06F16/185 ,  G06F16/2358

    Abstract: Methods and systems are described for receiving data including a hierarchy change log comprising change records specifying changes made to hierarchical data. The hierarchical data includes hierarchically arranged nodes. Change records are grouped according to a key corresponding to each record. Using a record consolidation algorithm, a consolidated view of the hierarchy change log is generated. A consolidated view can be generated by sorting, for each group, the change records into an ascending temporal order based on their respective timestamps to form a sequence of change records. The consolidated view is then displayed on an electronic visual display. Related apparatus, systems, techniques and articles are also described.

    Intelligent Outlier Data Detection
    6.
    发明申请
    Intelligent Outlier Data Detection 有权

    公开(公告)号：US20210182361A1

    公开(公告)日：2021-06-17

    申请号：US16711178

    申请日：2019-12-11

    Applicant: SAP SE

    Inventor： Kefeng Wang

    IPC: G06F17/18 ,  G06F16/903 ,  G06F11/32

    Abstract: Transaction data is received from a remote client computing device that includes user-generated entries in each of a plurality of fields. Thereafter, it can be determined, using an outlier detection algorithm, that values for one or more of the entries is an outlier. Data can then be provided (e.g., displayed in a visual display, loaded into memory, stored in physical persistence, transmitted to a remote computing system, etc.). The outlier algorithm can be based on a number of similar records g, a number of distinct values d(g) in the similar records, and a number of same values s in the similar records. Related apparatus, systems, techniques and articles are also described.

    EFFICIENT DATA RELATIONSHIP MINING USING MACHINE LEARNING
    7.
    发明申请
    EFFICIENT DATA RELATIONSHIP MINING USING MACHINE LEARNING 审中-公开

    公开(公告)号：US20200219006A1

    公开(公告)日：2020-07-09

    申请号：US16243845

    申请日：2019-01-09

    Applicant: SAP SE

    Inventor： Kefeng Wang

    IPC: G06N20/00 ,  G06F16/2458

    Abstract: Techniques and solutions are described for determining association rules using a machine learning technique on a subset of data to which the association rules might apply, and from which they can be determined. In particular, association rules are determined by tracking changes to attribute values of data objects having a type. The changed attribute value can be used as a consequent in an association rule. Values of other attributes of data objects having the changed attribute value can be used as antecedents in association rules. Values used in antecedents can be constrained, such as by limiting values to those associated with scope attributes or values satisfying a threshold occurrence frequency. In some cases, determined association rules can be automatically implemented, such as to process input or stored data for data objects of the type.

    Machine learning-based rule mining algorithm
    8.
    发明授权
    Machine learning-based rule mining algorithm 有权

    公开(公告)号：US11783205B2

    公开(公告)日：2023-10-10

    申请号：US16717819

    申请日：2019-12-17

    Applicant: SAP SE

    Inventor： Kefeng Wang ,  Andreas Seifried ,  Birgitta Bruegel ,  Kieran Turley ,  Dimitrij Raev

    IPC: G06N5/025 ,  G06N20/00

    CPC classification number: G06N5/025 ,  G06N20/00

    Abstract: Data is received that defines a rule mining run including a scope of a search and at least one data source to be searched. In response, the at least one data source is polled to obtain rules responsive to the rule mining run. Each rule can specify one or more actions to take as part of a computer-implemented process when certain conditions are met. A list of rules (i.e., a proposed subset of the obtained rules) can then be generated using at least one machine learning model. The generated list of rule can then be displayed in a graphical user interface. Related apparatus, systems, techniques and articles are also described.

    Efficient data relationship mining using machine learning
    9.
    发明授权
    Efficient data relationship mining using machine learning 有权

    公开(公告)号：US11556838B2

    公开(公告)日：2023-01-17

    申请号：US16243845

    申请日：2019-01-09

    Applicant: SAP SE

    Inventor： Kefeng Wang

    IPC: G06N20/00 ,  G06F16/2458

    Abstract: Techniques and solutions are described for determining association rules using a machine learning technique on a subset of data to which the association rules might apply, and from which they can be determined. In particular, association rules are determined by tracking changes to attribute values of data objects having a type. The changed attribute value can be used as a consequent in an association rule. Values of other attributes of data objects having the changed attribute value can be used as antecedents in association rules. Values used in antecedents can be constrained, such as by limiting values to those associated with scope attributes or values satisfying a threshold occurrence frequency. In some cases, determined association rules can be automatically implemented, such as to process input or stored data for data objects of the type.

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