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    • 1. 发明授权
    • Sponsored search data structure
    • 赞助搜索数据结构
    • US08606627B2
    • 2013-12-10
    • US12137567
    • 2008-06-12
    • Arnd Christian KönigMartin Miroslavov MarkovKenneth Ward Church
    • Arnd Christian KönigMartin Miroslavov MarkovKenneth Ward Church
    • G06Q40/00G07G1/14
    • G06Q30/02G06Q30/0246G06Q30/0256
    • A system that facilitates selecting advertisements that match a search query is described herein. The system includes a search query receiver component that receives a search query including keywords. The system also includes a match component that uses an associative data structure to identify in the associative data structure one or more data nodes that are associated in the associative data structure with respective unique keys corresponding to respective one or more hashes of combinations of the keywords in the search query. For each identified data node, the match component selects advertisements associated with bid phrases stored in the identified data node that respectively only include keywords included in the search query.
    • 这里描述了便于选择与搜索查询匹配的广告的系统。 该系统包括接收包括关键字的搜索查询的搜索查询接收器组件。 该系统还包括匹配组件,其使用关联数据结构来在关联数据结构中标识在关联数据结构中关联的一个或多个数据节点以及相应的唯一密钥,该唯一密钥对应于关键字的组合的相应一个或多个哈希值 搜索查询。 对于每个识别的数据节点,匹配组件选择与标识数据节点中存储的分别仅包括在搜索查询中的关键字相关联的出价短语相关联的广告。
    • 2. 发明授权
    • Reducing human overhead in text categorization
    • 在文本分类中减少人为的开销
    • US07894677B2
    • 2011-02-22
    • US11350701
    • 2006-02-09
    • Arnd Christian KönigEric D. Brill
    • Arnd Christian KönigEric D. Brill
    • G06K9/64
    • G06K9/6282
    • A unique multi-stage classification system and method that facilitates reducing human resources or costs associated with text classification while still obtaining a desired level of accuracy is provided. The multi-stage classification system and method involve a pattern-based classifier and a machine learning classifier. The pattern-based classifier is trained on discriminative patterns as identified by humans rather than machines which allow a smaller training set to be employed. Given humans' superior abilities to reason over text, discriminative patterns can be more accurately and more readily identified by them. Unlabeled items can be initially processed by the pattern-based classifier and if no pattern match exists, then the unlabeled data can be processed by the machine learning classifier. By employing the classifiers in this manner, less human involvement is required in the classification process. Even more, classification accuracy is maintained and/or improved.
    • 提供了一种独特的多级分类系统和方法,其有助于减少与文本分类相关联的人力资源或成本,同时仍然获得期望的精度水平。 多级分类系统和方法涉及基于模式的分类器和机器学习分类器。 对基于模式的分类器进行人类识别的识别模式的培训,而不是允许使用较小训练集的机器。 鉴于人类超越文本的优越能力,歧视性模式可以更准确,更容易地被识别。 未标记的项目可以由基于模式的分类器最初处理,如果不存在模式匹配,那么未标记的数据可以由机器学习分类器处理。 通过以这种方式使用分类器,在分类过程中需要较少的人参与。 更重要的是,维护和/或改进分类精度。
    • 8. 发明授权
    • Determination of landmarks
    • 确定地标
    • US09189488B2
    • 2015-11-17
    • US13081497
    • 2011-04-07
    • Mark S. ManasseArnd Christian KönigPaul Adrian Oltean
    • Mark S. ManasseArnd Christian KönigPaul Adrian Oltean
    • G06F17/30G06F21/10
    • G06F17/30156G06F21/10
    • Hash values corresponding to a file are processed in windows to determine a minimum hash value for each window. Each window may begin at a minimum hash value determined for a previous window and end after a fixed number of hash values. If a hash value is less than a threshold hash value, it is added to a buffer that is used to store the hash values in sorted order for a current window. If a hash value is greater than the threshold, it is added to another buffer whose hash values are not stored in sorted order. At the end of the current window, the minimum hash value in the first buffer is selected as the landmark for the window. If the first buffer is empty, then the hash values in the other buffer are sorted and the minimum hash value is selected as the landmark for the window.
    • 在窗口中处理与文件相对应的哈希值,以确定每个窗口的最小哈希值。 每个窗口可以以对于前一窗口确定的最小散列值开始,并在固定数量的散列值之后结束。 如果哈希值小于阈值哈希值,则将其添加到缓冲区中,该缓冲区用于按当前窗口的排序顺序存储哈希值。 如果哈希值大于阈值,则将其添加到另一个缓冲区,其哈希值不按排序顺序存储。 在当前窗口的末尾,第一个缓冲区中的最小哈希值被选为窗口的里程碑。 如果第一个缓冲区为空,则另一个缓冲区中的哈希值被排序,并选择最小哈希值作为窗口的标志。
    • 10. 发明申请
    • DETERMINATION OF LANDMARKS
    • 确定地名
    • US20120259897A1
    • 2012-10-11
    • US13081497
    • 2011-04-07
    • Mark S. ManasseArnd Christian KönigPaul Adrian Oltean
    • Mark S. ManasseArnd Christian KönigPaul Adrian Oltean
    • G06F17/30
    • G06F17/30156G06F21/10
    • Hash values corresponding to a file are processed in windows to determine a minimum hash value for each window. Each window may begin at a minimum hash value determined for a previous window and end after a fixed number of hash values. If a hash value is less than a threshold hash value, it is added to a buffer that is used to store the hash values in sorted order for a current window. If a hash value is greater than the threshold, it is added to another buffer whose hash values are not stored in sorted order. At the end of the current window, the minimum hash value in the first buffer is selected as the landmark for the window. If the first buffer is empty, then the hash values in the other buffer are sorted and the minimum hash value is selected as the landmark for the window.
    • 在窗口中处理与文件相对应的哈希值,以确定每个窗口的最小哈希值。 每个窗口可以以对于前一窗口确定的最小散列值开始,并在固定数量的散列值之后结束。 如果哈希值小于阈值哈希值,则将其添加到缓冲区中,该缓冲区用于按当前窗口的排序顺序存储哈希值。 如果哈希值大于阈值,则将其添加到另一个缓冲区,其哈希值不按排序顺序存储。 在当前窗口的末尾,第一个缓冲区中的最小哈希值被选为窗口的里程碑。 如果第一个缓冲区为空,则另一个缓冲区中的哈希值被排序,并选择最小哈希值作为窗口的里程碑。