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    • 2. 发明授权
    • Methods and systems of testing software, and methods and systems of modeling user behavior
    • 测试软件的方法和系统,以及用户行为建模的方法和系统
    • US07464372B2
    • 2008-12-09
    • US11188606
    • 2005-07-25
    • Dimitris AchlioptasChristian H. BorgsJennifer T. ChayesHenry J. RobinsonJames R. Tierney
    • Dimitris AchlioptasChristian H. BorgsJennifer T. ChayesHenry J. RobinsonJames R. Tierney
    • G06F9/44
    • G06F11/3688
    • Methods and systems of testing software and modeling user actions are described. In some embodiments, multiple different algorithms are provided for operating on a software model. The software model describes behavior associated with software that is to be tested. Different sets of algorithms can be selected for operating on the software model to produce a sequence of test actions that are to be used to test the software. The algorithms can be mixed and matched to achieve a desired testing result. In some embodiments, the different algorithms comprise deterministic algorithms, random algorithms, and various types of algorithms therebetween. In one embodiment, the software model comprises a state graph having nodes that represent state, and links between the nodes that represent actions. The different algorithms that are available for selection can have different graph traversal characteristics such that the state graph can be traversed in different manners. For example, algorithms that are more local in their traversals can be teamed with algorithms that are more global in their traversals, thus covering a wider area of the state space with good local coverage in some areas.
    • 描述测试软件和建模用户动作的方法和系统。 在一些实施例中,提供了用于在软件模型上操作的多种不同的算法。 软件模型描述与要测试的软件相关的行为。 可以选择不同的算法集来在软件模型上操作以产生用于测试软件的测试动作序列。 可以混合和匹配算法以实现所需的测试结果。 在一些实施例中,不同的算法包括确定性算法,随机算法以及它们之间的各种类型的算法。 在一个实施例中,软件模型包括具有表示状态的节点和表示动作的节点之间的链接的状态图。 可用于选择的不同算法可以具有不同的图遍历特性,使得可以以不同的方式遍历状态图。 例如,在遍历中更本地化的算法可以与在遍历中更全局化的算法相结合,从而在某些区域覆盖了更广泛的状态空间区域,具有良好的本地覆盖。
    • 9. 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。