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    • 2. 发明申请
    • Confusion matrix for classification systems
    • 分类系统混淆矩阵
    • US20080154807A1
    • 2008-06-26
    • US11644172
    • 2006-12-22
    • Jyh-Herng ChowByron DomDao-I Lin
    • Jyh-Herng ChowByron DomDao-I Lin
    • G06F15/18
    • G06K9/6253
    • Techniques are described herein for generating and displaying a confusion matrix wherein a data item belonging to one or more actual classes is predicted into a class. The classes in which the data item may be predicted (the “predicted classes”) are ranked according to a score that in one embodiment indicates the confidence of the prediction. If the data item is predicted into a class that is one of the top K ranked predicted classes, then the prediction is considered accurate and an entry is created in a cell of a confusion matrix indicating the accurate prediction. If the data item is not predicted into a class that is not one of the top K ranked predicted classes, then the prediction is considered inaccurate and an entry is created in a cell of a confusion matrix indicating the inaccurate prediction.
    • 本文描述了用于生成和显示混淆矩阵的技术,其中属于一个或多个实际类的数据项被预测为类。 可以根据在一个实施例中指示预测的置信度的分数对可以预测数据项目的类别(“预测类别”)进行排名。 如果数据项目被预测为属于顶级K级预测类别之一的类别,那么该预测被认为是准确的,并且在混合矩阵的小区中创建表示准确预测的条目。 如果数据项目未被预测为不属于顶级K级预测类别的类别,那么该预测被认为是不准确的,并且在混淆矩阵的小区中创建表示不准确预测的条目。
    • 4. 发明申请
    • Assigning into one set of categories information that has been assigned to other sets of categories
    • 分配到一组类别已经分配给其他类别的类别的信息
    • US20070214140A1
    • 2007-09-13
    • US11373726
    • 2006-03-10
    • Byron DomHui HanRamnath BalasubramanyanDmitry Pavlov
    • Byron DomHui HanRamnath BalasubramanyanDmitry Pavlov
    • G06F7/00
    • G06F17/30707
    • Techniques are described for assigning, to target categories of a target scheme, items that have been obtained from a plurality of sources. In situations in which one or more of the sources has organized its information according to a source scheme that differs from the target scheme, the assignment may be based, in part, on an estimate of the probability that items from a particular source category should be assigned to a particular target category. Such probability estimates may be based on how many training set items associated with the particular source category have been assigned to the particular target category. Source categories may be grouped into clusters. The probability estimates may also be based on how many training set items within the cluster to which the particular source category has been mapped, have been assigned the particular target category.
    • 描述了将目标方案的目标类别分配给从多个源获得的项目的技术。 在一个或多个来源已经根据与目标方案不同的源方案来组织其信息的情况下,分配可以部分地基于来自特定源类别的项目应该是 分配到特定目标类别。 这种概率估计可以基于与特定源类别相关联的多少训练集项目已被分配给特定目标类别。 源类别可以分组成簇。 概率估计还可以基于特定源类别已映射到的集群内的多少个训练集项目已被分配给特定的目标类别。
    • 5. 发明申请
    • STATISTICAL CREDIBILITY METRIC FOR ONLINE QUESTION ANSWERERS
    • 统计学可信度度量在线问题答案
    • US20120196266A1
    • 2012-08-02
    • US13443834
    • 2012-04-10
    • Byron DomDeepa Paranjpe
    • Byron DomDeepa Paranjpe
    • G09B7/00
    • G09B7/02G06Q10/0639G06Q30/0201G06Q30/0204
    • Techniques for statistically estimating a rating or other “figure of merit” for a user are disclosed. According to one such technique, a first quantity of submissions that were submitted by a user is determined. A second quantity of submissions that (a) were submitted by the user and (b) obtained a particular rating from a rating mechanism also is determined. A user rating for the user is determined based at least in part on the first quantity, the second quantity, and a factor that is independent of both the first quantity and the second quantity—such as the probability that an answer submitted by any answerer in a population will obtain the particular rating from the rating mechanism. The influence that the second quantity has on the user rating relative to the influence that the factor has on the user rating may depend at least in part on the first quantity.
    • 公开了用于统计估计用户的等级或其他“品质因数”的技术。 根据一种这样的技术,确定由用户提交的第一数量的提交。 (a)由用户提交的第二数量的提交(b)从评级机制获得特定评级也被确定。 至少部分地基于第一数量,第二数量和独立于第一数量和第二数量的因素来确定用户的用户评级,例如由任何回答者提交的答复的概率 人口将从评级机制中获得特定评级。 第二数量对用户评级的影响相对于该因素对用户评级的影响可能至少部分取决于第一数量。
    • 8. 发明授权
    • Statistical credibility metric for online question answerers
    • 在线问答员的统计信誉指标
    • US08155998B2
    • 2012-04-10
    • US11583413
    • 2006-10-18
    • Byron DomDeepa Paranjpe
    • Byron DomDeepa Paranjpe
    • G06Q10/00
    • G09B7/02G06Q10/0639G06Q30/0201G06Q30/0204
    • Techniques for statistically estimating a rating or other “figure of merit” for a user are disclosed. According to one such technique, a first quantity of submissions that were submitted by a user is determined. A second quantity of submissions that (a) were submitted by the user and (b) obtained a particular rating from a rating mechanism also is determined. A user rating for the user is determined based at least in part on the first quantity, the second quantity, and a factor that is independent of both the first quantity and the second quantity—such as the probability that an answer submitted by any answerer in a population will obtain the particular rating from the rating mechanism. The influence that the second quantity has on the user rating relative to the influence that the factor has on the user rating may depend at least in part on the first quantity.
    • 公开了用于统计估计用户的等级或其他“品质因数”的技术。 根据一种这样的技术,确定由用户提交的第一数量的提交。 (a)由用户提交的第二数量的提交(b)从评级机制获得特定评级也被确定。 至少部分地基于第一数量,第二数量和独立于第一数量和第二数量的因子来确定用户的用户评级,例如由任何回答者提交的答复的概率 人口将从评级机制中获得特定评级。 第二数量对用户评级的影响相对于该因素对用户评级的影响可能至少部分取决于第一数量。