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    • 9. 发明申请
    • AUTOMATED RECOGNITION OF PROCESS MODELING SEMANTICS IN FLOW DIAGRAMS
    • 流程图自动识别过程建模语言
    • US20120062574A1
    • 2012-03-15
    • US12881120
    • 2010-09-13
    • Pankaj DhooliaJuhnyoung LeeDebdoot MukherjeeAubrey J. Rembert
    • Pankaj DhooliaJuhnyoung LeeDebdoot MukherjeeAubrey J. Rembert
    • G06T1/20
    • G06K9/00476G06F8/10G06F8/20G06F8/30
    • An example embodiment disclosed is a system for automated model extraction of documents containing flow diagrams. An extractor is configured to extract from the flow diagrams flow graphs. The extractor further extracts nodes and edges, and relational, geometric and textual features for the extracted nodes and edges. A classifier is configured to recognize process semantics based on the extracted nodes and edges, and the relational, geometric and textual features of the extracted nodes and edges. A process modeling language code is generated based on the recognized process semantics. Rules to recognize patterns in process diagrams may be determined using supervised learning and/or unsupervised learning. During supervised learning, an expert labels example flow diagrams so that a classifier can derive the classification rules. During unsupervised learning flow diagrams are clustered based on relational, geometric and textual features of nodes and edges.
    • 所公开的示例性实施例是用于自动模型提取包含流程图的文档的系统。 提取器被配置为从流程图流程图中提取。 提取器进一步提取节点和边缘,以及提取的节点和边缘的关系,几何和文本特征。 分类器被配置为基于提取的节点和边缘以及提取的节点和边缘的关系,几何和文本特征来识别进程语义。 基于识别的流程语义生成流程建模语言代码。 可以使用监督学习和/或无监督学习来确定在过程图中识别模式的规则。 在监督学习期间,专家标签示例流程图,使得分类器可以导出分类规则。 在无监督的学习流程图中,基于节点和边缘的关系,几何和文本特征进行聚类。
    • 10. 发明授权
    • Automated recognition of process modeling semantics in flow diagrams
    • 流程图中过程建模语义的自动识别
    • US09087236B2
    • 2015-07-21
    • US12881120
    • 2010-09-13
    • Pankaj DhooliaJuhnyoung LeeDebdoot MukherjeeAubrey J. Rembert
    • Pankaj DhooliaJuhnyoung LeeDebdoot MukherjeeAubrey J. Rembert
    • G06F9/44G06K9/00
    • G06K9/00476G06F8/10G06F8/20G06F8/30
    • An example embodiment disclosed is a system for automated model extraction of documents containing flow diagrams. An extractor is configured to extract from the flow diagrams flow graphs. The extractor further extracts nodes and edges, and relational, geometric and textual features for the extracted nodes and edges. A classifier is configured to recognize process semantics based on the extracted nodes and edges, and the relational, geometric and textual features of the extracted nodes and edges. A process modeling language code is generated based on the recognized process semantics. Rules to recognize patterns in process diagrams may be determined using supervised learning and/or unsupervised learning. During supervised learning, an expert labels example flow diagrams so that a classifier can derive the classification rules. During unsupervised learning flow diagrams are clustered based on relational, geometric and textual features of nodes and edges.
    • 所公开的示例实施例是用于自动模型提取包含流程图的文档的系统。 提取器被配置为从流程图流程图中提取。 提取器进一步提取节点和边缘,以及提取的节点和边缘的关系,几何和文本特征。 分类器被配置为基于提取的节点和边缘以及提取的节点和边缘的关系,几何和文本特征来识别进程语义。 基于识别的流程语义生成流程建模语言代码。 可以使用监督学习和/或无监督学习来确定在过程图中识别模式的规则。 在监督学习期间,专家标签示例流程图,使得分类器可以导出分类规则。 在无监督的学习流程图中,基于节点和边缘的关系,几何和文本特征进行聚类。