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    • 1. 发明申请
    • METHOD AND SYSTEM FOR FAST SIMILARITY COMPUTATION IN HIGH DIMENSIONAL SPACE
    • 用于在高维空间中快速相似计算的方法和系统
    • US20130031059A1
    • 2013-01-31
    • US13189696
    • 2011-07-25
    • Shanmugasundaram RavikumarAnirban DasguptaTamas Sarlos
    • Shanmugasundaram RavikumarAnirban DasguptaTamas Sarlos
    • G06F17/30
    • G06F17/30628
    • Method, system, and programs for computing similarity. Input data is first received from one or more data sources and then analyzed to obtain an input feature vector that characterizes the input data. An index is then generated based on the input feature vector and is used to archive the input data, where the value of the index is computed based on an improved Johnson-Lindenstrass transformation (FJLT) process. With the improved FJLT process, first, the sign of each feature in the input feature vector is randomly flipped to obtain a flipped vector. A Hadamard transformation is then applied to the flipped vector to obtain a transformed vector. An inner product between the transformed vector and a sparse vector is then computed to obtain a base vector, based on which the value of the index is determined.
    • 用于计算相似度的方法,系统和程序。 首先从一个或多个数据源接收输入数据,然后分析以获得表征输入数据的输入特征向量。 然后基于输入特征向量生成索引,并且用于存档输入数据,其中基于改进的约翰逊 - 林登斯特拉斯变换(FJLT)处理来计算索引的值。 随着改进的FJLT过程,首先,输入特征向量中的每个特征的符号被随机翻转以获得翻转矢量。 然后将Hadamard变换应用于翻转矢量以获得变换矢量。 然后计算变换向量和稀疏向量之间的内积,以获得基准向量,基于此确定索引的值。
    • 2. 发明授权
    • Method and system for fast similarity computation in high dimensional space
    • 高维空间快速相似度计算方法与系统
    • US08515964B2
    • 2013-08-20
    • US13189696
    • 2011-07-25
    • Shanmugasundaram RavikumarAnirban DasguptaTamas Sarlos
    • Shanmugasundaram RavikumarAnirban DasguptaTamas Sarlos
    • G06F17/30
    • G06F17/30628
    • Method, system, and programs for computing similarity. Input data is first received from one or more data sources and then analyzed to obtain an input feature vector that characterizes the input data. An index is then generated based on the input feature vector and is used to archive the input data, where the value of the index is computed based on an improved Johnson-Lindenstrass transformation (FJLT) process. With the improved FJLT process, first, the sign of each feature in the input feature vector is randomly flipped to obtain a flipped vector. A Hadamard transformation is then applied to the flipped vector to obtain a transformed vector. An inner product between the transformed vector and a sparse vector is then computed to obtain a base vector, based on which the value of the index is determined.
    • 用于计算相似度的方法,系统和程序。 首先从一个或多个数据源接收输入数据,然后分析以获得表征输入数据的输入特征向量。 然后基于输入特征向量生成索引,并且用于存档输入数据,其中基于改进的约翰逊 - 林登斯特拉斯变换(FJLT)处理来计算索引的值。 随着改进的FJLT过程,首先,输入特征向量中的每个特征的符号被随机翻转以获得翻转矢量。 然后将Hadamard变换应用于翻转矢量以获得变换矢量。 然后计算变换向量和稀疏向量之间的内积,以获得基准向量,基于此确定索引的值。
    • 5. 发明申请
    • APPARATUS AND METHODS FOR LOSSLESS COMPRESSION OF NUMERICAL ATTRIBUTES IN RULE BASED SYSTEMS
    • 在基于规则的系统中数字属性的无损压缩的装置和方法
    • US20090210470A1
    • 2009-08-20
    • US12031127
    • 2008-02-14
    • Tamas SarlosJon Rexford Degenhardt
    • Tamas SarlosJon Rexford Degenhardt
    • G06F17/14G06N5/02
    • G06N5/025G06K9/6282
    • Disclosed are apparatus and methods for compressing a set of numerical values for a set of feature values, which can be utilized by a rule based or decision tree system. In certain embodiments, the numerical values are transformed into a subset of integer values based on how they are to be analyzed by conditional processes of the rule based or decision tree system that compare such numerical values to one or more threshold values. This transformation is accomplished such that if the rule based or decision tree system is applied after transformation, identical results are produced as compared to the original numerical values being used by the rule based or decision tree system. Other compression techniques may also be applied to the transformed values. An altered rule based or decision tree system, in which threshold values are also transformed to integer values, may be applied to the transformed values. Alternatively, the rule based or decision tree system may be applied to a set of decoded numerical values.
    • 公开了用于压缩一组特征值的一组数值的装置和方法,其可以由基于规则或决策树系统使用。 在某些实施例中,基于如何通过将这些数值与一个或多个阈值进行比较的基于规则或决策树系统的条件处理来将数值转换成整数值的子集。 完成这种转换,使得如果在转换之后应用基于规则或决策树系统,则与基于规则或决策树系统使用的原始数值相比产生相同的结果。 其他压缩技术也可以应用于变换值。 也可以将改变的基于规则或决策树系统(其中阈值也被转换为整数值)应用于转换的值。 或者,基于规则或决策树系统可以应用于一组解码的数值。
    • 8. 发明授权
    • Apparatus and methods for lossless compression of numerical attributes in rule based systems
    • 基于规则的系统中数值属性无损压缩的装置和方法
    • US08650144B2
    • 2014-02-11
    • US12031127
    • 2008-02-14
    • Tamas SarlosJon Rexford Degenhardt
    • Tamas SarlosJon Rexford Degenhardt
    • G06F17/00G06N5/02
    • G06N5/025G06K9/6282
    • Disclosed are apparatus and methods for compressing a set of numerical values for a set of feature values, which can be utilized by a rule based or decision tree system. In certain embodiments, the numerical values are transformed into a subset of integer values based on how they are to be analyzed by conditional processes of the rule based or decision tree system that compare such numerical values to one or more threshold values. This transformation is accomplished such that if the rule based or decision tree system is applied after transformation, identical results are produced as compared to the original numerical values being used by the rule based or decision tree system. Other compression techniques may also be applied to the transformed values. An altered rule based or decision tree system, in which threshold values are also transformed to integer values, may be applied to the transformed values. Alternatively, the rule based or decision tree system may be applied to a set of decoded numerical values.
    • 公开了用于压缩一组特征值的一组数值的装置和方法,其可以由基于规则或决策树系统使用。 在某些实施例中,基于如何通过将这些数值与一个或多个阈值进行比较的基于规则或决策树系统的条件处理来将数值转换成整数值的子集。 完成这种转换,使得如果在转换之后应用基于规则或决策树系统,则与基于规则或决策树系统使用的原始数值相比产生相同的结果。 其他压缩技术也可以应用于变换值。 也可以将改变的基于规则或决策树系统(其中阈值也被转换为整数值)应用于转换的值。 或者,基于规则或决策树系统可以应用于一组解码的数值。