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    • 2. 发明申请
    • Semantic and Contextual Searching of Knowledge Repositories
    • 知识库的语义和情境搜索
    • US20130144889A1
    • 2013-06-06
    • US13310868
    • 2011-12-05
    • Monika GuptaDebdoot MukherjeeSenthil K. ManiVibha S. Sinha
    • Monika GuptaDebdoot MukherjeeSenthil K. ManiVibha S. Sinha
    • G06F17/30
    • G06F17/30675
    • A system and an article of manufacture for semantic and contextual searching over a knowledge repository including creating a search query for each concept related to the target concept to form a search context, wherein the search query for each related concept comprises at least one word derived from a record of that concept previously authored in the project, running the search query on a search index of a knowledge repository to identify a record of the related concept for which the search query is created, and fetching the record of the target concept from the repository as a search result such that the fetched record of the target concept is linked in the knowledge repository to a record of the related concept returned as a result of running the search query on at least one record of the at least one related concept.
    • 一种用于在知识库中进行语义和上下文搜索的系统和制品,包括为与目标概念相关的每个概念创建搜索查询以形成搜索上下文,其中针对每个相关概念的搜索查询包括至少一个从 在该项目中创建的该概念的记录,在知识库的搜索索引上运行搜索查询,以识别创建搜索查询的相关概念的记录,以及从存储库中获取目标概念的记录 作为搜索结果,使得所获取的目标概念的记录在知识库中被链接到作为对至少一个相关概念的至少一个记录运行搜索查询的结果返回的相关概念的记录。
    • 3. 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。