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    • 1. 发明授权
    • Metadata search results ranking system
    • 元数据搜索结果排名系统
    • US06546388B1
    • 2003-04-08
    • US09483344
    • 2000-01-14
    • Stefan B. EdlundMichael L. EmensReiner KraftJussi MyllymakiShanghua Teng
    • Stefan B. EdlundMichael L. EmensReiner KraftJussi MyllymakiShanghua Teng
    • G06F1730
    • G06F17/30864Y10S707/99931Y10S707/99932Y10S707/99933Y10S707/99934Y10S707/99935
    • A method for presenting to an end-user the intermediate matching search results of a keyword search in an index list of information. The method comprising the steps of: coupling to a search engine a graphical user interface for accepting keyword search terms for searching the indexed list of information with the search engine; receiving one or more keyword search terms with one or more separation characters separating there between; performing a keyword search with the one or more keyword search terms received when a separation character is received; and presenting the number of documents matching the keyword search terms to the end-user presenting a graphical menu item on a display. A system and method of metadata search ranking is disclosed. The present invention utilizes a combination of popularity and/or relevancy to determine a search ranking for a given search result association.
    • 一种用于向最终用户呈现信息索引列表中的关键字搜索的中间匹配搜索结果的方法。 该方法包括以下步骤:将与图形用户界面相耦合的图形用户接口,用于接收关键词搜索项,用于搜索索引的信息列表; 接收一个或多个关键词搜索词与一个或多个分离字符之间的分隔符; 当接收到分离字符时,用所接收的一个或多个关键字搜索项执行关键字搜索; 以及将与关键字搜索项匹配的文档的数量呈现给在显示器上呈现图形菜单项的最终用户。 公开了一种元数据搜索排名的系统和方法。 本发明利用流行度和/或相关性的组合来确定给定搜索结果关联的搜索排名。
    • 2. 发明授权
    • Metadata search results ranking system
    • 元数据搜索结果排名系统
    • US06718324B2
    • 2004-04-06
    • US10354751
    • 2003-01-30
    • Stefan B. EdlundMichael L. EmensReiner KraftJussi MyllymakiShanghua Teng
    • Stefan B. EdlundMichael L. EmensReiner KraftJussi MyllymakiShanghua Teng
    • G06F1730
    • G06F17/30864Y10S707/99931Y10S707/99932Y10S707/99933Y10S707/99934Y10S707/99935
    • A system and method of metadata search ranking is disclosed. The present invention utilizes a combination of popularity and/or relevancy to determine a search ranking for a given search result association. Given the exponential growth rate currently being experienced in the Internet community, the present invention provides one of the few methods by which searches of this vast distributed database can produce useful results ranked and sorted by usefulness to the searching web surfer. The present invention permits embodiments incorporating a Ranking System/Method (0100) further comprising a Session Manager (0101), Query Manager (0102), Popularity Sorter (0103), and Association (0104) functions. These components may be augmented in some preferred embodiments via the use of a Query Entry means (0155), Search Engine (0156); Data Repository (0157), Query Database (0158), and/or a Resource List (0159).
    • 公开了一种元数据搜索排名的系统和方法。 本发明利用流行度和/或相关性的组合来确定给定搜索结果关联的搜索排名。 鉴于互联网社群目前正在经历的指数级增长率,本发明提供了这种广泛的分布式数据库的搜索可以产生按照搜索网络冲浪者的有用性排序和排序的有用结果的少数几种方法之一。 本发明允许包括排序系统/方法(0100)的实施例进一步包括会话管理器(0101),查询管理器(0102),流行分类器(0103)和关联(0104))功能。 在一些优选实施例中,可以通过使用查询输入装置(0155),搜索引擎(0156)来增加这些组件。 数据存储库(0157),查询数据库(0158)和/或资源列表(0159)。
    • 3. 发明授权
    • Detecting overlapping clusters
    • 检测重叠集群
    • US08949237B2
    • 2015-02-03
    • US13345593
    • 2012-01-06
    • Maria Florina BalcanChristian H. BorgsMark BravermanJennifer T. ChayesShanghua Teng
    • Maria Florina BalcanChristian H. BorgsMark BravermanJennifer T. ChayesShanghua Teng
    • G06F7/00G06F17/30
    • G06F17/30867G06Q10/10G06Q50/01
    • A technique for identifying overlapping clusters of items in a data set. The technique may be used in connection with a social network or other on-line environment in which users express approval for other users, such as through votes, tags or other inputs. These expressions of approval may be used to form clusters such that entities assigned to a cluster have a higher metric of approval from other entities within the cluster than from outside the cluster. Such clusters may be arrived at through a computationally efficient approach that involves randomly selecting one or more entities as a seed for a cluster. The cluster may be grown by testing other entities, similar to those already in the cluster, to determine whether they are more preferred by those already in the cluster than those outside the cluster. Once a cluster is grown to a desired size, it may be pruned.
    • 一种用于识别数据集中项目重叠聚类的技术。 该技术可以与社交网络或其他在线环境一起使用,其中用户通过投票,标签或其他输入来表达对其他用户的批准。 这些批准表达式可用于形成集群,使得分配给集群的实体具有比群集内外的其他实体更高的批准度量。 可以通过涉及随机选择一个或多个实体作为集群的种子的计算有效的方法来获得这样的集群。 可以通过测试类似于集群中的那些其他实体来生成集群,以确定它们是否比集群以外的集群更为优先。 一旦群集生长到所需的大小,它可能被修剪。
    • 4. 发明申请
    • DETECTING OVERLAPPING CLUSTERS
    • 检测重叠群集
    • US20130179449A1
    • 2013-07-11
    • US13345593
    • 2012-01-06
    • Maria Florina BalcanChristian H. BorgsMark BravermanJennifer T. ChayesShanghua Teng
    • Maria Florina BalcanChristian H. BorgsMark BravermanJennifer T. ChayesShanghua Teng
    • G06F17/30
    • G06F17/30867G06Q10/10G06Q50/01
    • A technique for identifying overlapping clusters of items in a data set. The technique may be used in connection with a social network or other on-line environment in which users express approval for other users, such as through votes, tags or other inputs. These expressions of approval may be used to form clusters such that entities assigned to a cluster have a higher metric of approval from other entities within the cluster than from outside the cluster. Such clusters may be arrived at through a computationally efficient approach that involves randomly selecting one or more entities as a seed for a cluster. The to cluster may be grown by testing other entities, similar to those already in the cluster, to determine whether they are more preferred by those already in the cluster than those outside the cluster. Once a cluster is grown to a desired size, it may be pruned.
    • 一种用于识别数据集中项目重叠聚类的技术。 该技术可以与社交网络或其他在线环境一起使用,其中用户通过投票,标签或其他输入来表达对其他用户的批准。 这些批准表达式可用于形成集群,使得分配给集群的实体具有比群集内外的其他实体更高的批准度量。 可以通过涉及随机选择一个或多个实体作为集群的种子的计算有效的方法来获得这样的集群。 可以通过测试与群集中已经存在的其他实体类似的其他实体来生成集群,以确定它们是否比集群以外的已经在群集中更为优先。 一旦群集生长到所需的大小,它可能被修剪。