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    DETECTING DEVIATIONS BETWEEN EVENT LOG AND PROCESS MODEL
    11.
    发明申请
    DETECTING DEVIATIONS BETWEEN EVENT LOG AND PROCESS MODEL 审中-公开

    公开(公告)号：US20150302314A1

    公开(公告)日：2015-10-22

    申请号：US14748867

    申请日：2015-06-24

    Applicant: International Business Machines Corporation

    Inventor： Jing Li ,  Xiang Li ,  Haifeng Liu ,  Guo Tong Xie ,  Yi Qin Yu ,  Shi Lei Zhang

    IPC: G06N7/00

    Abstract: A method for detecting deviations between an event log and a process model includes converting the process model into a probability process model, the probability process model comprising multiple nodes in multiple hierarchies and probability distribution associated with the multiple nodes, a leaf node among the multiple nodes corresponding to an activity in the process model; detecting differences between at least one event sequence contained in the event log and the probability process model according to a correspondence relationship; and identifying the differences as the deviations in response to the differences exceeding a predefined threshold; wherein the correspondence relationship describes a correspondence relationship between an event in one event sequence of the at least one event sequence and a leaf node in the probability process model.

    Domain adaptation
    12.
    发明授权
    Domain adaptation 有权

    公开(公告)号：US12254062B2

    公开(公告)日：2025-03-18

    申请号：US17003104

    申请日：2020-08-26

    Applicant: International Business Machines Corporation

    Inventor： Yi Qin Yu ,  Shiwan Zhao ,  Jing Mei ,  Shao Chun Li ,  Xu Min

    IPC: G06N20/00 ,  G06F18/214 ,  G06F18/22 ,  G06F18/2431 ,  G06N3/08 ,  G16H10/60

    Abstract: Embodiments of the present disclosure relate to a method, system, and computer program product for domain adaptation. According to the method, a source model of a source domain is obtained, where the source model is trained to generate a label indicating a predicted category of data from the source domain. A training sample from a target domain is obtained, where the training sample comprises training data from the target domain and a true label indicating a true category of the training data from the target domain. A first label is generated for the training data by using the source model. The first label indicates a predicted category of the training data. A target model of the target domain is trained based on the training data, the true label and the first label.

    Detecting deviations between event log and process model
    16.
    发明授权
    Detecting deviations between event log and process model 有权

    公开(公告)号：US10474956B2

    公开(公告)日：2019-11-12

    申请号：US14748850

    申请日：2015-06-24

    Applicant: International Business Machines Corporation

    Inventor： Jing Li ,  Xiang Li ,  Haifeng Liu ,  Guo Tong Xie ,  Yi Qin Yu ,  Shi Lei Zhang

    IPC: G06N7/00

    Abstract: A method for detecting deviations between an event log and a process model includes converting the process model into a probability process model, the probability process model comprising multiple nodes in multiple hierarchies and probability distribution associated with the multiple nodes, a leaf node among the multiple nodes corresponding to an activity in the process model; detecting differences between at least one event sequence contained in the event log and the probability process model according to a correspondence relationship; and identifying the differences as the deviations in response to the differences exceeding a predefined threshold; wherein the correspondence relationship describes a correspondence relationship between an event in one event sequence of the at least one event sequence and a leaf node in the probability process model.

    Dynamic code suggestion
    17.
    发明授权
    Dynamic code suggestion 有权

    公开(公告)号：US10437565B2

    公开(公告)日：2019-10-08

    申请号：US15252960

    申请日：2016-08-31

    Applicant: International Business Machines Corporation

    Inventor： Bi Bo Hao ,  Gang Hu ,  Jing Li ,  Wen Sun ,  Guo Tong Xie ,  Yi Qin Yu

    IPC: G06F8/33

    Abstract: This disclosure provides a computer-implemented method for code suggestion. The method comprises collecting a set of runtime context features of a program that is being edited. The method further comprises comparing the set of runtime context features with at least one set of stored context features to find at least one matching set of stored context features. Each of the at least one set of stored context features is extracted from a corresponding code segment. The method further comprises presenting at least one code segment with its set of stored context features matching the set of runtime context features, for the user to choose to add into the program.

    Hypothesis derived from relationship graph
    19.
    发明授权
    Hypothesis derived from relationship graph 有权
    从关系图导出的假设

    公开(公告)号：US09043256B2

    公开(公告)日：2015-05-26

    申请号：US13688323

    申请日：2012-11-29

    Applicant: International Business Machines Corporation

    Inventor： Yue Pan ,  Wei Jia Shen ,  Xing Zhi Sun ,  Xiao Fei Teng ,  Lin Hao Xu ,  Yi Qin Yu ,  Yu Chen Zhou

    IPC: G06N5/00 ,  G06F7/60 ,  G06N5/02

    CPC classification number: G06N5/02 ,  G06N5/003

    Abstract: A method and apparatus for data processing. The method calculates correlations between a plurality of attributes in a dataset. The attributes are factors involved in transaction processing. The method generates a relationship graph by using the plurality of attributes and the correlations between the plurality of attributes; and extracts a sub-graph from the relationship graph to represent a hypothesis. The hypothesis describes the impacts of the factors on the transaction processing. Also provided is an apparatus for implementing the above data processing method.

    Abstract translation: 一种用于数据处理的方法和装置。 该方法计算数据集中的多个属性之间的相关性。 这些属性是事务处理中涉及到的因素。 该方法通过使用多个属性和多个属性之间的相关性来生成关系图; 并从关系图提取子图以表示假设。 该假设描述了因素对交易处理的影响。 还提供了一种用于实现上述数据处理方法的装置。

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