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    • 3. 发明授权
    • Interactive framework for name disambiguation
    • 互动框架的名称消歧
    • US08538898B2
    • 2013-09-17
    • US13118404
    • 2011-05-28
    • Zhengdong LuZaiqing NieGang LuoYong CaoJi-Rong WenWei-Ying Ma
    • Zhengdong LuZaiqing NieGang LuoYong CaoJi-Rong WenWei-Ying Ma
    • G06N5/00
    • G06N99/005G06F17/30616
    • A “Name Disambiguator” provides various techniques for implementing an interactive framework for resolving or disambiguating entity names (associated with objects such as publications) for entity searches where two or more same or similar names may refer to different entities. More specifically, the Name Disambiguator uses a combination of user input and automatic models to address the disambiguation problem. In various embodiments, the Name Disambiguator uses a two part process, including: 1) a global SVM trained from large sets of documents or objects in a simulated interactive mode, and 2) further personalization of local SVM models (associated with individual names or groups of names such as, for example, a group of coauthors) derived from the global SVM model. The result of this process is that large sets of documents or objects are rapidly and accurately condensed or clustered into ordered sets by that are organized by entity names.
    • “名称歧义者”提供了各种技术,用于实现用于解析或消除实体名称(与诸如出版物的对象相关联)的交互式框架,用于实体搜索,其中两个或多个相同或相似的名称可以指代不同的实体。 更具体地说,名称消歧器使用用户输入和自动模型的组合来解决消歧问题。 在各种实施例中,名称消歧器使用两部分过程,包括:1)以模拟交互模式从大量文档或对象训练的全局SVM,以及2)本地SVM模型的进一步个性化(与个体名称或组相关联 来自全球SVM模型的名称,例如一组合作者。 这个过程的结果是,大量的文档或对象可以通过按实体名称组织的快速,准确的浓缩或聚类成有序集。
    • 4. 发明申请
    • INTERACTIVE FRAMEWORK FOR NAME DISAMBIGUATION
    • 名称撤销的互动框架
    • US20120303557A1
    • 2012-11-29
    • US13118404
    • 2011-05-28
    • Zhengdong LuZaiqing NieGang LuoYong CaoJi-Rong WenWei-Ying Ma
    • Zhengdong LuZaiqing NieGang LuoYong CaoJi-Rong WenWei-Ying Ma
    • G06F15/18
    • G06N99/005G06F17/30616
    • A “Name Disambiguator” provides various techniques for implementing an interactive framework for resolving or disambiguating entity names (associated with objects such as publications) for entity searches where two or more same or similar names may refer to different entities. More specifically, the Name Disambiguator uses a combination of user input and automatic models to address the disambiguation problem. In various embodiments, the Name Disambiguator uses a two part process, including: 1) a global SVM trained from large sets of documents or objects in a simulated interactive mode, and 2) further personalization of local SVM models (associated with individual names or groups of names such as, for example, a group of coauthors) derived from the global SVM model. The result of this process is that large sets of documents or objects are rapidly and accurately condensed or clustered into ordered sets by that are organized by entity names.
    • 名称消歧者提供各种技术,用于实现用于解析或消除实体名称(与诸如出版物的对象相关联)的交互式框架,用于实体搜索,其中两个或多个相同或相似的名称可以指代不同的实体。 更具体地说,名称消歧器使用用户输入和自动模型的组合来解决消歧问题。 在各种实施例中,名称消歧器使用两部分过程,包括:1)以模拟交互模式从大量文档或对象训练的全局SVM,以及2)本地SVM模型的进一步个性化(与个体名称或组相关联 来自全球SVM模型的名称,例如一组合作者。 这个过程的结果是,大量的文档或对象可以通过按实体名称组织的快速,准确的浓缩或聚类成有序集。
    • 10. 发明授权
    • Webpage entity extraction through joint understanding of page structures and sentences
    • 网页实体提取通过联合理解页面结构和句子
    • US09092424B2
    • 2015-07-28
    • US12569912
    • 2009-09-30
    • Zaiqing NieYong CaoJi-Rong WenChunyu Yang
    • Zaiqing NieYong CaoJi-Rong WenChunyu Yang
    • G06F17/00G06F17/27
    • G06F17/278
    • Described is a technology for understanding entities of a webpage, e.g., to label the entities on the webpage. An iterative and bidirectional framework processes a webpage, including a text understanding component (e.g., extended Semi-CRF model) that provides text segmentation features to a structure understanding component (e.g., extended HCRF model). The structure understanding component uses the text segmentation features and visual layout features of the webpage to identify a structure (e.g., labeled block). The text understanding component in turn uses the labeled block to further understand the text. The process continues iteratively until a similarity criterion is met, at which time the entities may be labeled. Also described is the use of multiple mentions of a set of text in the webpage to help in labeling an entity.
    • 描述了一种用于理解网页的实体的技术,例如标记网页上的实体。 迭代和双向框架处理网页,包括向结构理解组件(例如,扩展HCRF模型)提供文本分段特征的文本理解组件(例如,扩展Semi-CRF模型)。 结构理解组件使用网页的文本分割特征和视觉布局特征来识别结构(例如,标记块)。 文本理解组件依次使用标记块来进一步理解文本。 该过程继续迭代直到满足相似性标准,此时实体可以被标记。 还描述了使用多个提及网页中的一组文本来帮助标注一个实体。