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    Detecting patterns that increase the risk of late delivery of a software project
    1.
    发明授权
    Detecting patterns that increase the risk of late delivery of a software project 有权
    检测增加软件项目延迟交付风险的模式

    公开(公告)号：US09563864B2

    公开(公告)日：2017-02-07

    申请号：US14178995

    申请日：2014-02-12

    Applicant: International Business Machines Corporation

    Inventor： Murray R. Cantor ,  Evelyn Duesterwald ,  Tamir Klinger ,  Peter K. Malkin ,  Paul M. Matchen ,  Stanley M. Sutton ,  Peri L. Tarr ,  Mark N. Wegman

    IPC: G06Q10/06

    CPC classification number: G06Q10/063114 ,  G06Q10/06 ,  G06Q10/06312 ,  G06Q10/06313 ,  G06Q10/0633 ,  G06Q10/0635

    Abstract: Historic and current development data associated with the project may be gathered. A catalog of patterns, each pattern associated with a data measure and an analysis routine capable of detecting the pattern according to the data measure in a given data set may be obtained. A pattern describes a particular indication in the historical and development data, which arises one or more of, at a discrete point in time or over a period of time. The analysis routine may be applied to the historic and current development data. A notification may be issued responsive to identifying the pattern in the historic and current development data. The applying and the issuing may be performed for each pattern in the catalog of patterns.

    Abstract translation: 可能收集与该项目相关的历史和当前开发数据。 可以获得模式目录，与数据测量相关联的每个模式和能够根据给定数据集中的数据测量来检测模式的分析程序。 模式描述历史和发展数据中的特定指示，其在离散的时间点或一段时间内产生一个或多个。 分析程序可以应用于历史和当前的开发数据。 响应于识别历史和当前开发数据中的模式，可以发出通知。 可以对模式目录中的每个模式执行应用和发行。

    Learning neuro-symbolic multi-hop reasoning rules over text
    3.
    发明授权
    Learning neuro-symbolic multi-hop reasoning rules over text 有权

    公开(公告)号：US11645526B2

    公开(公告)日：2023-05-09

    申请号：US16911645

    申请日：2020-06-25

    Applicant: International Business Machines Corporation

    Inventor： Mo Yu ,  Li Zhang ,  Tamir Klinger ,  Xiaoxiao Guo

    IPC: G06N3/08 ,  G06N3/044

    CPC classification number: G06N3/08 ,  G06N3/044

    Abstract: A method and a system for learning and applying neuro-symbolic multi-hop rules are provided. The method includes inputting training texts into a neural network as well as pre-defined entities. The training texts and the entities relate to a specific domain. The method also includes generating an entity graph made up of nodes and edges. The nodes represent the pre-defined entities, and the edges represent passages in the training texts with co-occurrence of the entities connected together by the edges. The method further includes determining a relation based on the passages for each of the pre-defined entities connected together by the edges, calculating a probability relating to the relation, generating a potential reasoning path between a head entity and a target entity. The method also includes learning a neuro-symbolic rule by converting the edges along the potential reasoning path into symbolic rules and combining those rules into the neuro-symbolic rule.

    Automated intelligent data navigation and prediction tool
    4.
    发明授权
    Automated intelligent data navigation and prediction tool 有权

    公开(公告)号：US10572819B2

    公开(公告)日：2020-02-25

    申请号：US14812344

    申请日：2015-07-29

    Applicant: International Business Machines Corporation

    Inventor： Tamir Klinger ,  Chandrasekhara K. Reddy ,  Ashish Sabharwal ,  Horst C. Samulowitz ,  Gerald J. Tesauro ,  Deepak S. Turaga

    IPC: G06N5/04 ,  G06N20/00

    Abstract: A system, method, and computer program product for automatically selecting from a plurality of analytic algorithms a best performing analytic algorithm to apply to a dataset is provided. The automatically selecting from the plurality of analytic algorithms the best performing analytic algorithm to apply to the dataset enables a training a plurality of analytic algorithms on a plurality of subsets of the dataset. Then, a corresponding prediction accuracy trend is estimated across the subsets for each of the plurality of analytic algorithms to produce a plurality of accuracy trends. Next, the best performing analytic algorithm is selected and outputted from the plurality of analytic algorithms based on the corresponding prediction accuracy trend with a highest value from the plurality of accuracy trends.

    SYSTEM AND METHOD FOR AUTOMATICALLY DETERMINING RELATIONSHIPS BETWEEN SOFTWARE ARTIFACTS USING MULTIPLE EVIDENCE SOURCES
    7.
    发明申请
    SYSTEM AND METHOD FOR AUTOMATICALLY DETERMINING RELATIONSHIPS BETWEEN SOFTWARE ARTIFACTS USING MULTIPLE EVIDENCE SOURCES 有权
    使用多个证据来源自动确定软件作品之间的关系的系统和方法

    公开(公告)号：US20150149983A1

    公开(公告)日：2015-05-28

    申请号：US14614864

    申请日：2015-02-05

    Applicant: International Business Machines Corporation

    Inventor： Tamir Klinger ,  Peri L. Tarr

    IPC: G06F17/50 ,  G06F11/36 ,  G06F9/445 ,  G06F9/44

    CPC classification number: G06F17/50 ,  G06F8/10 ,  G06F8/20 ,  G06F8/654 ,  G06F8/70 ,  G06F8/71 ,  G06F8/74 ,  G06F8/75 ,  G06F11/3476 ,  G06F11/3684

    Abstract: A method (which can be computer implemented) for inferring whether at least a first relationship exists between at least first and second entities includes the steps of applying a first assessor to obtain a first confidence level pertaining to putative existence of said at least first relationship between said at least first and second entities, applying a second assessor to obtain a second confidence level pertaining to putative existence of said at least first relationship between said at least first and second entities, and combining said first and second confidence levels to obtain an overall inference whether said at least first relationship exists between said at least first and second entities.

    Abstract translation: 一种用于推断至少第一和第二实体之间是否至少存在第一关系的方法（其可以是计算机实现的）包括以下步骤：应用第一评估者以获得与所述至少第一关系的推定存在有关的第一置信水平 至少第一和第二实体表示，应用第二评估者以获得与所述至少第一和第二实体之间的所述至少第一关系的推定存在相关的第二置信水平，以及组合所述第一和第二置信水平以获得总体推断 是否在所述至少第一和第二实体之间存在至少第一关系。

    Exploring the impact of changing project parameters on the likely delivery date of a project
    10.
    发明授权
    Exploring the impact of changing project parameters on the likely delivery date of a project 有权
    探索改变项目参数对项目可能交付日期的影响

    公开(公告)号：US09501753B2

    公开(公告)日：2016-11-22

    申请号：US14179140

    申请日：2014-02-12

    Applicant: International Business Machines Corporation

    Inventor： Murray R. Cantor ,  Evelyn Duesterwald ,  Tamir Klinger ,  Peter K. Malkin ,  Paul M. Matchen ,  Stanley M. Sutton ,  Peri L. Tarr ,  Mark N. Wegman

    IPC: G06Q10/06

    CPC classification number: G06Q10/063114 ,  G06Q10/06 ,  G06Q10/06312 ,  G06Q10/06313 ,  G06Q10/0633 ,  G06Q10/0635

    Abstract: A user may be allowed to specify a change in one or more parameter data associated with the project, the one or more parameter data used previously to compute a probability distribution of completion time of the project. The probability distribution of completion time of the project may be recomputed based on the change. The recomputed probability distribution of the completion time of the project may be presented. An option to save the recomputed probability distribution may be provided. An option may be provided to specify another change in one or more parameter data associated with the project and repeat the recomputing and the presenting procedures based on another change in one or more parameter data associated with the project.

    Abstract translation: 可以允许用户指定与项目相关联的一个或多个参数数据中的变化，即先前使用的用于计算项目完成时间的概率分布的一个或多个参数数据。 项目完成时间的概率分布可以根据变更重新计算。 项目完成时间的重新计算概率分布可以被提出。 可以提供保存重新计算的概率分布的选项。 可以提供选项来指定与项目相关联的一个或多个参数数据中的另一变化，并且基于与项目相关联的一个或多个参数数据中的另一变化重复重新计算和呈现过程。

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