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    • 7. 发明授权
    • Symbol grouping and recognition in expression recognition
    • 表达识别中的符号分组和识别
    • US07561738B2
    • 2009-07-14
    • US11155614
    • 2005-06-20
    • Yu ZouLei HuangJian-Lai ZhouMingqing XuYue LiXiaohui HouDongmei ZhangJian Wang
    • Yu ZouLei HuangJian-Lai ZhouMingqing XuYue LiXiaohui HouDongmei ZhangJian Wang
    • G06K9/18
    • G06K9/222
    • A mechanism for recognizing and inputting handwritten mathematical expressions into a computer by providing a part of a multi-path framework is described. The part of the multi-path framework includes a symbol grouping and recognition component that is designed to group input strokes that correspond to a handwritten mathematical expression into a symbol and to recognize the symbol based upon information associated with the grouped input strokes. A method for grouping and recognizing symbols of a handwritten mathematical expression includes receiving a plurality of input strokes corresponding to a handwritten mathematical expression, grouping the plurality of input strokes into symbols, recognizing the symbols based upon information, such as shape and time series information, associated with the grouped input strokes. Intra-group and inter-group information associated with the plurality of input strokes may be utilized to group the input strokes.
    • 描述了通过提供多路径框架的一部分来将手写数学表达式识别并输入到计算机中的机制。 多路径框架的一部分包括符号分组和识别组件,其被设计为将对应于手写数学表达式的输入笔划分组到符号中,并且基于与分组的输入笔画相关联的信息来识别符号。 一种用于分组和识别手写数学表达符号的方法包括:接收与手写数学表达式对应的多个输入笔画,将多个输入笔划分组成符号,基于诸如形状和时间序列信息的信息识别符号, 与分组的输入笔画相关联。 可以利用与多个输入笔画相关联的组内和组间信息来对输入笔画进行分组。
    • 9. 发明申请
    • INFERRING OPINIONS BASED ON LEARNED PROBABILITIES
    • 基于认知可行性的感染意见
    • US20080097758A1
    • 2008-04-24
    • US11552057
    • 2006-10-23
    • Hua LiJian-Lai ZhouZheng ChenJian WangDongmei Zhang
    • Hua LiJian-Lai ZhouZheng ChenJian WangDongmei Zhang
    • G10L15/00
    • G06F17/2715G06Q30/02G06Q30/0217G06Q30/0282
    • An opinion system infers the opinion of a sentence of a product review based on a probability that the sentence contains certain sequences of parts of speech that are commonly used to express an opinion as indicated by the training data and the probabilities of the training data. When provided with the sentence, the opinion system identifies possible sequences of parts of speech of the sentence that are commonly used to express an opinion and the probability that the sequence is the correct sequence for the sentence. For each sequence, the opinion system then retrieves a probability derived from the training data that the sequence contains an opinion word that expresses an opinion. The opinion system then retrieves a probability from the training data that the opinion words of the sentence are used to express an opinion. The opinion system then combines the probabilities to generate an overall probability that the sentence with that sequence expresses an opinion.
    • 意见系统根据该训练数据和训练数据概率所指示的句子包含通常用于表达意见的特定词汇序列的概率来推断产品评论的句子的意见。 当提供句子时,意见系统识别通常用于表达意见的句子的部分语音的可能序列以及序列是句子的正确序列的概率。 对于每个序列,意见系统然后检索从训练数据得出的概率,该序列包含表达意见的意见词。 然后,意见系统从训练数据中检索出用于表达意见的句子意见词的概率。 然后,意见系统将概率组合以产生具有该序列的句子表达意见的总体概率。