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1.发明授权System and method for generating taxonomies with applications to content-based recommendations 有权用于生成基于内容的建议的分类法的系统和方法公开(公告)号：US06360227B1
公开(公告)日：2002-03-19
申请号：US09240231
申请日：1999-01-29
IPC分类号： G06F1700
CPC分类号： G06F17/30873 , Y10S707/99935 , Y10S707/99943 , Y10S707/99944
摘要： A graph taxonomy of information which is represented by a plurality of vectors is generated. The graph taxonomy includes a plurality of nodes and a plurality of edges. The plurality of nodes is generated, and each node of the plurality of nodes is associated with ones of the plurality of vectors. A tree hierarchy is established based on the plurality of nodes. A plurality of distances between ones of the plurality of nodes is calculated. Ones of the plurality of nodes are connected with other ones of the plurality of nodes by ones of the plurality of edges based on the plurality of distances. The information represented by the plurality of vectors may be, for example, a plurality of documents such as Web Pages.
摘要翻译： 生成由多个向量表示的信息的图分类法。 图形分类法包括多个节点和多个边缘。 生成多个节点，并且多个节点中的每个节点与多个向量中的每个节点相关联。 基于多个节点建立树层次结构。 计算多个节点中的多个节点之间的多个距离。 基于多个距离，多个节点中的一个与多个节点中的其他节点通过多个边缘中的一个连接。 由多个向量表示的信息可以是例如多个文档，例如网页。
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公开(公告)号：US06263327B1
公开(公告)日：2001-07-17
申请号：US09522723
申请日：2000-03-10
IPC分类号： G06F1700
CPC分类号： G06F17/30893 , G06F17/30386 , G06F17/3056 , Y10S707/99931 , Y10S707/99936
摘要： A computerized method of online mining of inference rules in a large database. The method is comprised of two stages, a preprocessing stage followed by an online rule generation stage. The pro-processing stage is further defined to be a two step process that involves the generation of large itemsets. The present method defines large itemsets by how the items in the itemsets relate to each other rather than their level of presence. The measure by which itemsets are said to relate to each other is defined by a computed figure of merit, K1. The first substep of the preprocessing stage involves finding those itemsets that possess a minimum computer collective strength of K1. From those found itemsets, a second user supplied input, K2 is used to prune those itemsets with inference strength below K2.
摘要翻译： 一种在大型数据库中在线挖掘推理规则的计算机化方法。 该方法由两个阶段组成，一个预处理阶段，随后是在线规则生成阶段。 前处理阶段被进一步定义为涉及生成大项目集的两步过程。 本方法通过项目集中的项目相互关联而不是其存在级别来定义大项目集。 项目集被称为相互关联的措施由计算出的品质因数K1定义。 预处理阶段的第一个子步骤是找到具有最小计算机集体实力K1的项目集。 从那些找到的项目集中，第二个用户提供输入，K2用于修剪低于K2的推理强度的项目集。
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公开(公告)号：US6092064A
公开(公告)日：2000-07-18
申请号：US964064
申请日：1997-11-04
CPC分类号： G06F17/30613 , G06F17/30327 , G06F17/30539 , G06F17/30864 , Y10S707/954 , Y10S707/956 , Y10S707/968 , Y10S707/99932 , Y10S707/99936
摘要： A computer method of online mining of quantitative association rules consisting of two stages, a preprocessing stage followed by an online rule generation stage. The required computational effort is reduced by the pre-processing stage, defined by pre-processing data to organize the relationship between antecedent attributes to create a heirarchially arranged multidimensional indexing structure. The resulting structure facilitates the performance of the second stage, online processing, which involves the generation of quantitative association rules. The second stage, online rule generation, utilizes the multidimensional index structure created by the preprocessing stage by first finding the areas in the data which correspond to the rules and then uses a merging step to create a merged tree in order to carefully combine interesting regions in order to give a heirarchical representation of the rule set. The merged tree is then used in order to actually generate the rules.
摘要翻译： 一种在线挖掘定量关联规则的计算机方法，包括两个阶段，一个预处理阶段，随后是在线规则生成阶段。 通过预处理阶段来减少所需的计算量，该预处理阶段通过预处理数据来定义，以组织先行属性之间的关系，以创建一个历史性地排列的多维索引结构。 所产生的结构有助于第二阶段的在线处理，其涉及产生定量关联规则的性能。 第二阶段，在线规则生成，利用由预处理阶段创建的多维索引结构，首先查找与规则相对应的数据中的区域，然后使用合并步骤创建合并树，以便仔细地组合有趣区域 命令给出规则集的历史代表性。 然后使用合并的树来实际生成规则。
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4.发明授权公开(公告)号：US06289354B1
公开(公告)日：2001-09-11
申请号：US09167332
申请日：1998-10-07
IPC分类号： G06F1730
CPC分类号： G06F17/30598 , G06F17/30327 , Y10S707/99935 , Y10S707/99936 , Y10S707/99945 , Y10S707/99948
摘要： Information is analyzed in the form of a plurality of data values that represent a plurality of objects. A set of features that characterize each object of the plurality of objects is identified. The plurality of data values are stored in a database. Each data value corresponds to at least one of the plurality of objects based on the set of features. Ones of the plurality of data values stored in the database are partitioned into a plurality of clusters. Each cluster of the plurality of clusters is assigned to one respective node of a plurality of nodes arranged in a tree hierarchy. Ones of the plurality of nodes of the tree hierarchy are traversed. If desired, information may be analyzed for finding peer groups in e-commerce applications.
摘要翻译： 以表示多个对象的多个数据值的形式分析信息。 识别表征多个对象中的每个对象的一组特征。 多个数据值存储在数据库中。 基于特征集合，每个数据值对应于多个对象中的至少一个。 存储在数据库中的多个数据值的一部分被划分成多个簇。 将多个群集中的每个群集分配给以树状层次结构排列的多个节点的一个相应节点。 遍历树层次结构的多个节点的一部分。 如果需要，可以分析信息以在电子商务应用中寻找对等组。
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5.发明授权System and method for searching databases with applications such as peer groups, collaborative filtering, and e-commerce 有权用于通过对等组，协同过滤和电子商务等应用程序搜索数据库的系统和方法公开(公告)号：US06236985B1
公开(公告)日：2001-05-22
申请号：US09168117
申请日：1998-10-07
IPC分类号： G06F1730
CPC分类号： G06F17/30324 , G06Q40/04 , Y10S707/99932 , Y10S707/99936
摘要： A method of analyzing information in the form of a plurality of data records. Each data record includes one or more data values. The data values are partitioned into a plurality of data signatures. Data values of data signatures are compared to data values of data records. Based on the result of the comparison an index is associated with each data record. A bound corresponding to the index is calculated based on a user defined target value and an objective function. If desired, information may be analyzed for finding peer groups in e-commerce applications.
摘要翻译： 一种以多个数据记录的形式分析信息的方法。 每个数据记录包括一个或多个数据值。 数据值被划分成多个数据签名。 将数据签名的数据值与数据记录的数据值进行比较。 基于比较的结果，索引与每个数据记录相关联。 基于用户定义的目标值和目标函数计算与索引相对应的边界。 如果需要，可以分析信息以在电子商务应用中寻找对等组。
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6.发明授权Permutation based pyramid block transmission scheme for broadcasting in video-on-demand storage systems 失效在视频点播存储系统中广播的基于置换的金字塔块传输方案
公开(公告)号：US5751336A
公开(公告)日：1998-05-12
申请号：US542002
申请日：1995-10-12
IPC分类号： H04H20/40 , H04H40/09 , H04N7/173 , H04N21/472
CPC分类号： H04H20/16 , H04H20/40 , H04H40/09 , H04H60/06 , H04N21/47202 , H04N7/17318 , H04N7/17336
摘要： Portions of multimedia program (presentation) are repetitively broadcast to receiving stations with subsequent portions being broadcast less frequently than preceding portions. Blocks of at least one of the portions are broadcast in varying permutations from one repetition to a next repetition. Further, each portion is of a length which is proportional to a sum of the lengths of all preceding portions. A receiver is provided with selects blocks to be skipped (in a pyramid type broadcast) based on information indicative of the permutation selected by the server. The receiver determines the number of blocks to skip before buffering the next block for the video being viewed.
摘要翻译： 多媒体节目（呈现）的部分被重复地广播到接收站，其后续部分的广播频率比以前的部分要少。 至少一个部分的块在从一个重复到下一个重复的变化排列中被广播。 此外，每个部分的长度与所有先前部分的长度的总和成比例。 基于指示由服务器选择的置换的信息，向接收机提供要跳过（以金字塔型广播）的选择块。 接收器在缓冲正在观看的视频的下一个块之前确定要跳过的块数。
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公开(公告)号：US06307965B1
公开(公告)日：2001-10-23
申请号：US09070600
申请日：1998-04-30
IPC分类号： G06K962
CPC分类号： G06F17/30598 , G06F2216/03
摘要： A system and method are provided to analyze information stored in a computer data base by detecting clusters of related or correlated data values. Data values stored in the data base represent a set of objects. A data value is stored in the data base as an instance of a set of features that characterize the objects. The features are the dimensions of the feature space of the data base. Each cluster includes not only a subset of related data values stored in the data base but also a subset of features. The data values in a cluster are data values that are a short distance apart, in the sense of a metric, when projected onto a subspace that corresponds to the subset of features of the cluster. A set of k clusters may be detected such that the average number of features of the subsets of features of the clusters is l.
摘要翻译： 提供了一种系统和方法来通过检测相关或相关数据值的群集来分析存储在计算机数据库中的信息。 存储在数据库中的数据值表示一组对象。 数据值作为表征对象的一组特征的实例存储在数据库中。 特征是数据库的特征空间的尺寸。 每个簇不仅包括存储在数据库中的相关数据值的子集，而且还包括特征的子集。 当集群中的数据值被投影到与集群的特征子集相对应的子空间上时，在度量意义上是短距离的数据值。 可以检测一组k个群集，使得群集的特征子集的特征的平均数量为l。
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8.发明授权System and method for collaborative filtering with applications to e-commerce 有权用于电子商务应用程序的协同过滤的系统和方法公开(公告)号：US06487541B1
公开(公告)日：2002-11-26
申请号：US09236051
申请日：1999-01-22
IPC分类号： G06F1760
CPC分类号： G06Q30/02 , G06Q30/0201 , G06Q30/0241 , G06Q30/0601
摘要： A rating of a plurality of ratings is predicted. The rating is associated with a user of a plurality of users and the rating corresponds to an item of a plurality of items. One of the plurality of ratings, corresponding to at least one of the plurality of items, is provided for each of the plurality of users. A predictability relation between ones of the plurality of users and other ones of the plurality of users is calculated based on ratings provided by users. One of a plurality of nodes is assigned to each of the plurality of users. Ones of the plurality of nodes are connected with other ones of the plurality of nodes by a plurality of edges based on the predictability relation. A graph which includes the plurality of nodes and the plurality of edges is searched for a path from a node assigned to the user of the plurality of users to another node assigned to another user of the plurality of users. The rating of the plurality of ratings associated with the user of a plurality of users is calculated based on the path and the predictability relation. If desired, a predicted rating may be produced for identifying products and customers in an e-commerce applications.
摘要翻译： 预测多个等级的等级。 评级与多个用户的用户相关联，并且评级对应于多个项目的项目。 为多个用户中的每个用户提供对应于多个项目中的至少一个的多个评级中的一个。 基于用户提供的评级来计算多个用户中的一个和多个用户中的一个的可预测性关系。 将多个节点中的一个分配给多个用户中的每一个。 基于可预测性关系，多个节点的多个边缘与多个节点中的其他节点连接。 搜索包括多个节点和多个边缘的图形，从分配给多个用户的用户的节点到分配给多个用户的另一个用户的另一个节点的路径。 基于路径和可预测性关系来计算与多个用户的用户相关联的多个评级的评级。 如果需要，可以产生用于识别电子商务应用中的产品和客户的预测等级。
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9.发明授权System and method for detecting clusters of information with application to e-commerce 有权应用于电子商务的信息集群的系统和方法公开(公告)号：US06349309B1
公开(公告)日：2002-02-19
申请号：US09317472
申请日：1999-05-24
IPC分类号： G06F1730
CPC分类号： G06F17/30598 , Y10S707/99932 , Y10S707/99935 , Y10S707/99936
摘要： A method of analyzing information in the form of a plurality of data values. The plurality of data values represent a plurality of objects. The plurality of data values are distributed in a data space. A set of features which characterize each of the plurality of objects is identified. The plurality of data values are stored in a database. Each of the plurality of data values corresponds to at least one of the plurality of objects based on the set of features. Ones of the plurality of data values stored in the database are partitioned into a plurality of clusters. A respective orientation associated with a position in data space of data values which are contained in each respective cluster of the plurality of clusters is calculated based on the set of features. If desired, information may be analyzed for finding peer groups in e-commerce applications.
摘要翻译： 一种以多个数据值的形式分析信息的方法。 多个数据值表示多个对象。 多个数据值分布在数据空间中。 识别表征多个对象中的每一个的一组特征。 多个数据值存储在数据库中。 基于特征集合，多个数据值中的每一个对应于多个对象中的至少一个。 存储在数据库中的多个数据值的一部分被划分成多个簇。 基于特征集来计算与包含在多个群集的每个相应群集中的数据值的数据空间中的位置相关联的取向。 如果需要，可以分析信息以在电子商务应用中寻找对等组。
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10.发明授权Finding collective baskets and inference rules for internet or intranet mining for large data bases 失效为大型数据库查找互联网或内部网挖掘的集体篮子和推理规则
公开(公告)号：US6094645A
公开(公告)日：2000-07-25
申请号：US975603
申请日：1997-11-21
CPC分类号： G06F17/30893 , G06F17/30386 , G06F17/3056 , Y10S707/99931 , Y10S707/99936
摘要： A computer method of online mining of inference rules in a large database comprising a preprocessing stage and an online rule generation stage. The pre-processing stage includes first finding itemsets that possess a minimum computed collective strength K1, and second, pruning the itemsets with inference strength below a predetermined inference strength, K2. The online rule generation stage utilizes the itemsets organized into an adjacency lattice to generate inference rules with inference strength K2.
摘要翻译： 一种在大型数据库中在线挖掘推理规则的计算机方法，包括预处理阶段和在线规则生成阶段。 预处理阶段包括首先找到具有最小计算集体强度K1的项目集，以及其次，用低于预定推理强度K2的推理强度修剪项集。 在线规则生成阶段利用组织成邻接网格的项集来产生具有推理强度K2的推理规则。
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