-
公开(公告)号：US08661042B2
公开(公告)日：2014-02-25
申请号：US12906551
申请日：2010-10-18
CPC分类号： G06F17/30699
摘要： Systems, methods, and machine readable and executable instructions are provided for collaborative filtering. Collaborative filtering includes representing users and objects by rows and columns in a binary ratings matrix having a particular dimensional space. Unknown values in the binary ratings matrix are weighted with a weight matrix having the particular dimensional space. The binary ratings matrix and the weight matrix are hashed into a lower dimensional space by one of row and column. The hashed binary ratings matrix and the hashed weight matrix are low-rank approximated by alternating least squares. A result of the low-rank approximation for the one of row and column is updated using the binary ratings matrix and the weight matrix. A recommendation of one of the objects can be generated for one of the users based on the updated result.
摘要翻译： 提供系统，方法和机器可读和可执行指令用于协同过滤。 协同过滤包括用具有特定尺寸空间的二进制评级矩阵中的行和列来表示用户和对象。 二进制等级矩阵中的未知值用具有特定尺寸空间的权重矩阵加权。 二进制等级矩阵和权重矩阵通过行和列之一被散列成较低维的空间。 散列二进制等级矩阵和散列权重矩阵是通过交替的最小二乘法近似的低阶。 使用二进制等级矩阵和权重矩阵来更新行和列之一的低阶近似的结果。 可以基于更新的结果为一个用户生成其中一个对象的推荐。
-
公开(公告)号：US08631017B2
公开(公告)日：2014-01-14
申请号：US12970262
申请日：2010-12-16
CPC分类号： G06F17/3053
摘要： Systems, methods, and machine readable and executable instructions are provided for collaborative filtering. Collaborative filtering includes representing users and objects by rows and columns in an ordinal ratings matrix having a particular dimensional space. Values in the ordinal ratings matrix are weighted with a weight matrix having the particular dimensional space. The weight matrix is hashed into a lower dimensional space by one of row and column by multiplying a projection matrix by the weight matrix. The ordinal ratings matrix is hashed into a lower dimensional space by multiplying the projection matrix by an element-wise product of the weight matrix and the ordinal ratings matrix to form a reduced ratings matrix, and element-wise dividing the reduced ratings matrix by the hashed weight matrix. The hashed ordinal ratings matrix and the hashed weight matrix are low-rank approximated by alternating least squares. A result of the low-rank approximation for the one of row and column is updated using the ordinal ratings matrix and the weight matrix. A recommendation of one of the objects can be generated for one of the users based on the updated result.
摘要翻译： 提供系统，方法和机器可读和可执行指令用于协同过滤。 协作过滤包括用具有特定尺寸空间的序数等级矩阵中的行和列表示用户和对象。 使用具有特定尺寸空间的权重矩阵对序数等级矩阵中的值进行加权。 通过将投影矩阵乘以权重矩阵，权重矩阵通过行和列之一被散列成较低维空间。 通过将投影矩阵乘以权重矩阵和序数等级矩阵的元素乘积来将序数等级矩阵散列到较低维空间中，以形成减小的等级矩阵，并且将分数矩阵除以散列 重量矩阵。 散列序数等级矩阵和散列权重矩阵由交替的最小二乘法近似近似。 使用序数等级矩阵和权重矩阵来更新行和列之一的低阶近似的结果。 可以基于更新的结果为一个用户生成其中一个对象的推荐。
-
公开(公告)号：US20120158741A1
公开(公告)日：2012-06-21
申请号：US12970262
申请日：2010-12-16
IPC分类号： G06F17/30
CPC分类号： G06F17/3053
摘要： Systems, methods, and machine readable and executable instructions are provided for collaborative filtering. Collaborative filtering includes representing users and objects by rows and columns in an ordinal ratings matrix having a particular dimensional space. Values in the ordinal ratings matrix are weighted with a weight matrix having the particular dimensional space. The weight matrix is hashed into a lower dimensional space by one of row and column by multiplying a projection matrix by the weight matrix. The ordinal ratings matrix is hashed into a lower dimensional space by multiplying the projection matrix by an element-wise product of the weight matrix and the ordinal ratings matrix to form a reduced ratings matrix, and element-wise dividing the reduced ratings matrix by the hashed weight matrix. The hashed ordinal ratings matrix and the hashed weight matrix are low-rank approximated by alternating least squares. A result of the low-rank approximation for the one of row and column is updated using the ordinal ratings matrix and the weight matrix. A recommendation of one of the objects can be generated for one of the users based on the updated result.
摘要翻译： 提供系统，方法和机器可读和可执行指令用于协同过滤。 协作过滤包括用具有特定尺寸空间的序数等级矩阵中的行和列表示用户和对象。 使用具有特定尺寸空间的权重矩阵对序数等级矩阵中的值进行加权。 通过将投影矩阵乘以权重矩阵，权重矩阵通过行和列之一被散列成较低维空间。 通过将投影矩阵乘以权重矩阵和序数等级矩阵的元素乘积来将序数等级矩阵散列到较低维空间中，以形成减小的等级矩阵，并且将分数矩阵除以散列 重量矩阵。 散列序数等级矩阵和散列权重矩阵是通过交替的最小二乘法近似的低阶。 使用序数等级矩阵和权重矩阵来更新行和列之一的低阶近似的结果。 可以基于更新的结果为一个用户生成其中一个对象的推荐。
-
公开(公告)号：US20110113385A1
公开(公告)日：2011-05-12
申请号：US12614193
申请日：2009-11-06
IPC分类号： G06F3/048
CPC分类号： G06F17/30873
摘要： In a method of visually representing a hierarchy of category nodes that identify one or more concepts, accesses to documents are tracked and one or more concepts that are relevant to the accessed documents are determined. In addition, one or more category paths through the hierarchy of category nodes for the determined one or more concepts are determined and relevance levels for the category nodes with respect to the determined one or more concepts are determined based upon the generated one or more category paths. Moreover, a graph depicting a visual representation of the relevance levels determined for each of the category nodes in the hierarchy of category nodes is constructed.
摘要翻译： 在可视地表示标识一个或多个概念的类别节点的层次结构的方法中，跟踪对文档的访问，并确定与被访问文档相关的一个或多个概念。 此外，确定用于确定的一个或多个概念的通过类别节点的层次结构的一个或多个类别路径，并且基于所生成的一个或多个类别路径来确定关于所确定的一个或多个概念的类别节点的相关性级别 。 此外，构造描绘对于类别节点的层次结构中的每个类别节点确定的相关性级别的视觉表示的图形。
-
公开(公告)号：US20110112824A1
公开(公告)日：2011-05-12
申请号：US12614260
申请日：2009-11-06
IPC分类号： G06F17/27
CPC分类号： G06F17/27
摘要： In a method of determining at least one category path for identifying an input text, one or more categories that are most relevant to the input text are determined, one or more concepts that are most relevant to the input text using information from a labeled text data source and the one or more categories determined to be the most relevant to the input text are determined, and one or more category paths through a hierarchy of predefined category levels are determined for one or more of the determined concepts.
摘要翻译： 在确定用于识别输入文本的至少一个类别路径的方法中，确定与输入文本最相关的一个或多个类别，使用来自标记文本数据的信息与输入文本最相关的一个或多个概念 源和确定为与输入文本最相关的一个或多个类别，并且针对一个或多个所确定的概念确定通过预定类别级别的层级的一个或多个类别路径。
-
公开(公告)号：US08954893B2
公开(公告)日：2015-02-10
申请号：US12614193
申请日：2009-11-06
CPC分类号： G06F17/30873
摘要： In a method of visually representing a hierarchy of category nodes that identify one or more concepts, accesses to documents are tracked and one or more concepts that are relevant to the accessed documents are determined. In addition, one or more category paths through the hierarchy of category nodes for the determined one or more concepts are determined and relevance levels for the category nodes with respect to the determined one or more concepts are determined based upon the generated one or more category paths. Moreover, a graph depicting a visual representation of the relevance levels determined for each of the category nodes in the hierarchy of category nodes is constructed.
摘要翻译： 在可视地表示标识一个或多个概念的类别节点的层次结构的方法中，跟踪对文档的访问，并确定与被访问文档相关的一个或多个概念。 此外，确定用于确定的一个或多个概念的通过类别节点的层次结构的一个或多个类别路径，并且基于所生成的一个或多个类别路径来确定关于所确定的一个或多个概念的类别节点的相关性级别 。 此外，构造描绘对于类别节点的层次结构中的每个类别节点确定的相关性级别的视觉表示的图形。
-
公开(公告)号：US20120096009A1
公开(公告)日：2012-04-19
申请号：US12906551
申请日：2010-10-18
IPC分类号： G06F17/30
CPC分类号： G06F17/30699
摘要： Systems, methods, and machine readable and executable instructions are provided for collaborative filtering. Collaborative filtering includes representing users and objects by rows and columns in a binary ratings matrix having a particular dimensional space. Unknown values in the binary ratings matrix are weighted with a weight matrix having the particular dimensional space. The binary ratings matrix and the weight matrix are hashed into a lower dimensional space by one of row and column. The hashed binary ratings matrix and the hashed weight matrix are low-rank approximated by alternating least squares. A result of the low-rank approximation for the one of row and column is updated using the binary ratings matrix and the weight matrix. A recommendation of one of the objects can be generated for one of the users based on the updated result.
摘要翻译： 提供系统，方法和机器可读和可执行指令用于协同过滤。 协同过滤包括用具有特定尺寸空间的二进制评级矩阵中的行和列来表示用户和对象。 二进制等级矩阵中的未知值用具有特定尺寸空间的权重矩阵加权。 二进制等级矩阵和权重矩阵通过行和列之一被散列成较低维的空间。 散列二进制等级矩阵和散列权重矩阵是通过交替的最小二乘法近似的低阶。 使用二进制等级矩阵和权重矩阵来更新行和列之一的低阶近似的结果。 可以基于更新的结果为一个用户生成其中一个对象的推荐。
-
公开(公告)号：US09430562B2
公开(公告)日：2016-08-30
申请号：US12242752
申请日：2008-09-30
申请人： George Forman , Shyamsundar Rajaram
发明人： George Forman , Shyamsundar Rajaram
IPC分类号： G06F17/30
CPC分类号： G06F17/30705
摘要： Provided are, among other things, systems, methods and techniques for document-based processing. In one implementation, a document is input; features are extracted from it; an index is queried using at least a subset of the extracted features and, in response, identifications for selected document classifiers are received from a larger pool of document classifiers; the document is processed using individual ones of the selected document classifiers, thereby generating corresponding classifier outputs; and then, based on such classifier outputs, (1) the document is categorized within a computer database and/or (2) feedback information is provided to a user.
摘要翻译： 尤其是基于文档处理的系统，方法和技术。 在一个实现中，输入文档; 特征从中提取出来; 使用提取的特征的至少一个子集来查询索引，并且作为响应，从较大的文档分类器池接收所选择的文档分类器的标识; 使用所选择的文档分类器中的单独的文档分类器处理文档，从而生成相应的分类器输出; 然后，基于这样的分类器输出，（1）文档被分类在计算机数据库中和/或（2）向用户提供反馈信息。
-
公开(公告)号：US20100082642A1
公开(公告)日：2010-04-01
申请号：US12242752
申请日：2008-09-30
申请人： George Forman , Shyamsundar Rajaram
发明人： George Forman , Shyamsundar Rajaram
IPC分类号： G06F17/30
CPC分类号： G06F17/30705
摘要： Provided are, among other things, systems, methods and techniques for document-based processing. In one implementation, a document is input; features are extracted from it; an index is queried using at least a subset of the extracted features and, in response, identifications for selected document classifiers are received from a larger pool of document classifiers; the document is processed using individual ones of the selected document classifiers, thereby generating corresponding classifier outputs; and then, based on such classifier outputs, (1) the document is categorized within a computer database and/or (2) feedback information is provided to a user.
摘要翻译： 尤其是基于文档处理的系统，方法和技术。 在一个实现中，输入文档; 特征从中提取出来; 使用提取的特征的至少一个子集来查询索引，并且作为响应，从较大的文档分类器池接收所选择的文档分类器的标识; 使用所选择的文档分类器中的单独的文档分类器处理文档，从而生成相应的分类器输出; 然后，基于这样的分类器输出，（1）文档被分类在计算机数据库中和/或（2）向用户提供反馈信息。
-
公开(公告)号：US20100082579A1
公开(公告)日：2010-04-01
申请号：US12243075
申请日：2008-10-01
申请人： Shyamsundar Rajaram
发明人： Shyamsundar Rajaram
IPC分类号： G06F17/30
CPC分类号： G06F17/3033 , G06F17/30528 , G06F17/30598 , G06F17/30607 , G06F17/30864
摘要： Provided are, among other things, systems, methods and techniques for identifying matching objects in a computer database. In one representative technique, a set of attribute-value pairs corresponding to a query data object are input, with individual ones of the attribute-value pairs including an identified attribute and a value for the identified attribute; multiple characteristic fingerprints are assigned to individual ones of the attribute-value pairs in the set, the characteristic fingerprints having been selected from an attribute-specific field of available characteristic fingerprints based on the value for the identified attribute; a subset of at least one characteristic fingerprint is selected from across the characteristic fingerprints for the query data object, based on a selection criterion, and a database is queried using the subset of at least one characteristic fingerprint to identify any matches.
摘要翻译： 除其他之外，提供用于识别计算机数据库中的匹配对象的系统，方法和技术。 在一种代表性技术中，输入与查询数据对象对应的一组属性值对，其中属性值对中的各个属性值对包括识别的属性和所识别的属性的值; 将多个特征指纹分配给集合中的属性值对的各个特征指纹，基于所识别的属性的值，已经从可用特征指纹的属性特定字段中选择了特征指纹; 基于选择标准，从查询数据对象的特征指纹中选择至少一个特征指纹的子集，并且使用至少一个特征指纹的子集来查询数据库以识别任何匹配。
-
-
-
-
-
-
-
-
-
搜索结果
13 条记录 (耗时 0.017 秒)
