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    • 4. 发明授权
    • Method for a topic hierarchy classification system
    • 主题层次分类系统的方法
    • US06947936B1
    • 2005-09-20
    • US09846069
    • 2001-04-30
    • Henri Jacques SuermondtGeorge Henry Forman
    • Henri Jacques SuermondtGeorge Henry Forman
    • G06F17/30
    • G06F17/30707Y10S707/99932Y10S707/99933Y10S707/99937Y10S707/99938
    • A method and system is provided for categorization of an item. A plurality of categories is organized in a hierarchy of categories with a plurality of categorizers corresponding to the plurality of categories. A featurizer featurizes the item to create a list of item features. The list is used in a categorizer system, including the plurality of categorizers, for determining a plurality of levels of goodness. The item is categorized in the categorizer system in the plurality of categories based on the respective plurality of levels of goodness. The best categories are processed first, allowing termination at any time. The system successively refines an item down a hierarchy, until the features no longer support further refinement. The categories and the degree of support for the categories are provided.
    • 提供了一种用于对物品进行分类的方法和系统。 多个类别被组织在具有对应于多个类别的多个分类器的类别层级中。 功能特征使项目功能化,以创建项目功能列表。 列表在分类器系统中使用,包括多个分类器,用于确定多个良好级别。 基于相应的多个良好级别,将项目分类在多个类别中的分类器系统中。 首先处理最佳类别,允许任何时间终止。 系统连续地将一个项目细分为层次结构,直到特征不再支持进一步细化。 提供了类别和类别的支持程度。
    • 6. 发明授权
    • Hierarchical categorization method and system with automatic local selection of classifiers
    • 分层分类方法和自动选择分类器的系统
    • US07349917B2
    • 2008-03-25
    • US10262742
    • 2002-10-01
    • George Henry FormanHenri Jacques Suermondt
    • George Henry FormanHenri Jacques Suermondt
    • G06F7/00G06F17/00G06F15/18G06E1/00G06E3/00G06G7/00G06N5/02
    • G06F17/30705Y10S707/99943
    • The present invention relates generally to the classification of items into categories, and more generally, to the automatic selection of different classifiers at different places within a hierarchy of categories. An exemplary hierarchical categorization method uses a hybrid of different classification technologies, with training-data based machine-learning classifiers preferably being used in those portions of the hierarchy above a dynamically defined boundary in which adequate training data is available, and with a-priori classification rules not requiring any such training-data being used below that boundary, thereby providing a novel hybrid categorization technology that is capable of leveraging the strengths of its components. In particular, it enables the use of human-authored rules in those finely divided portions towards the bottom of the hierarchy involving relatively close decisions for which it is not practical to create in advance sufficient training data to ensure accurate classification by known machine-learning algorithms, while still facilitating eventual change-over within the hierarchy to machine learning algorithms as sufficient training data becomes available to ensure acceptable performance in a particular sub-portion of the hierarchy.
    • 本发明一般涉及将物品分类为类别,更一般地涉及在类别等级中的不同地点的不同分类器的自动选择。 示例性分层分类方法使用不同分类技术的混合,基于训练数据的机器学习分类器优选地在层次结构的那些部分中使用,其中动态定义的边界在其中具有足够的训练数据可用,并且具有先验分类 规则不要求在该边界之下使用任何此类培训数据,从而提供能够利用其组件优点的新型混合分类技术。 特别地,它使得能够将这些精细划分的部分中的人造作规则用于层次结构的底部,涉及相对较为紧密的决策,预先创建足够的训练数据以确保通过已知机器学习算法的准确分类是不实际的 同时仍然促进层次结构内的最终改变,以便在足够的训练数据变得可用以确保层次结构的特定子部分中可接受的性能时进行机器学习算法。
    • 7. 发明授权
    • Method of efficient migration from one categorization hierarchy to another hierarchy
    • 从一个分类层次到另一层次的有效迁移的方法
    • US06701333B2
    • 2004-03-02
    • US09908388
    • 2001-07-17
    • Henri Jacques SuermondtGeorge Henry Forman
    • Henri Jacques SuermondtGeorge Henry Forman
    • G06F1730
    • G06F17/3061Y10S707/99931Y10S707/99932Y10S707/99933Y10S707/99934Y10S707/99955
    • A method of efficiently migrating data from one categorization hierarchy to a new hierarchy. A mapping is created which describes where a document in one hierarchy will be placed in a new hierarchy. The classifier of the first hierarchy is merged with this mapping to act as a classifier for the second hierarchy. Cases from the first hierarchy are classified in the new hierarchy using this merged mapping. In another embodiment, a training set is designated from a first hierarchy and mapped to a second hierarchy. Using machine learning, a classifier for the second hierarchy is derived and used to classify subsequently migrated cases. Migration of data using the present invention is more accurate as fewer human errors are generated. The present invention can act as a virtual classifier for multiple hierarchies in an organization, providing updated categorization information for multiple hierarchical databases.
    • 有效地将数据从一个分类层次迁移到新的层次结构的方法。 创建一个映射,描述一个层次结构中的文档将放置在新层次结构中的位置。 第一层次的分类器与此映射合并,以充当第二层次的分类器。 使用此合并映射将来自第一层次的案例分类到新的层次结构中。 在另一个实施例中,从第一层次指定训练集并将其映射到第二层次。 使用机器学习,导出第二层次的分类器,并用于对随后迁移的案例进行分类。 使用本发明的数据的迁移更精确,因为产生较少的人为错误。 本发明可以用作组织中多层次的虚拟分类器,为多层次数据库提供更新的分类信息。