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公开(公告)号：US10152557B2
公开(公告)日：2018-12-11
申请号：US14278811
申请日：2014-05-15
Applicant: GOOGLE INC.
Inventor： Seyed Vahab Mirrokni Banadaki , Silvio Lattanzi , Jonathan Ezra Feldman , Alessandro Epasto , Stefano Leonardi , Hugh Lynch , Varun Sharma
Abstract: Systems and methods offer an efficient approach to computing similarity rankings in bipartite graphs. An example system includes at least one processor and memory storing a bipartite graph having a first set and a second set of nodes, with nodes in the first set being connected to nodes in the second set by edges. The memory also stores instructions that, when executed by the at least one processor, cause the system to assign each node in the second set to one of a plurality of categories and, for each of the plurality of categories, generate a subgraph. The subgraph comprises of a subset of nodes in the first set and edges linking the nodes in the subset, where the nodes in the subset are selected based on connection to a node in the second set that is assigned to the category. The system uses the subgraph to respond to queries.
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公开(公告)号：US09098819B1
公开(公告)日：2015-08-04
申请号：US13654589
申请日：2012-10-18
Applicant: Google Inc.
Inventor： Nitish Korula , Silvio Lattanzi , Ming Xiong
CPC classification number: G06Q10/0635 , G06F17/30864 , G06Q10/06 , G06Q10/10 , G06Q40/08 , G06Q50/01
Abstract: A system and method for determining matching pairs between social networks is disclosed. The system comprises a matching module that includes an account retrieval engine, candidate pairing module, a match determination module, a social network engine, a personalizing engine and a graphical user interface engine. The candidate pairing module generates candidate pairs of accounts from different social networks that may represent the same user. The match pairing module generates scores for the pairs. The match determination module determines a subset of the pairs that most likely represent the same users.
Abstract translation: 公开了一种用于确定社交网络之间的匹配对的系统和方法。 该系统包括一个匹配模块，包括一个帐户检索引擎，候选配对模块，匹配确定模块，社交网络引擎，个性化引擎和图形用户界面引擎。 候选配对模块从可能代表相同用户的不同社交网络产生候选对帐户对。 匹配配对模块生成成对的得分。 匹配确定模块确定最可能代表相同用户的对的子集。
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公开(公告)号：US09596295B2
公开(公告)日：2017-03-14
申请号：US14143894
申请日：2013-12-30
Applicant: GOOGLE INC.
Inventor： Seyed Vahab Mirrokni Banadaki , Raimondas Kiveris , Vibhor Rastogi , Silvio Lattanzi , Sergei Vassilvitskii
CPC classification number: H04L67/10 , G06F9/5066 , G06F9/546 , G06Q10/06
Abstract: Systems and methods for improving the time and cost to calculate connected components in a distributed graph are disclosed. One method includes reducing a quantity of map-reduce rounds used to determine a cluster assignment for a node in a large distributed graph by alternating between two hashing functions in the map stage of a map-reduce round and storing the cluster assignment for the node in a memory. Another method includes reducing a quantity of messages sent during map-reduce rounds by performing a predetermined quantity of rounds to generate, for each node, a set of potential cluster assignments, generating a data structure in memory to store a mapping between each node and its potential cluster assignment, and using the data structure during remaining map-reduce rounds, wherein the remaining map-reduce rounds do not send messages between nodes. The method can also include storing the cluster assignment for the node in a memory.
Abstract translation: 公开了用于改善计算分布图中的连接部件的时间和成本的系统和方法。 一种方法包括通过在map-reduce round的映射阶段中的两个散列函数之间交替并且将节点的集群分配存储在减少用于确定大分布式图中的节点的集群分配的地图缩小轮数量 一个记忆 另一种方法包括通过执行预定量的轮次来减少在地图缩小轮期间发送的消息的数量，以为每个节点生成一组潜在的分组分配，在存储器中生成数据结构以存储每个节点与其之间的映射 潜在的集群分配，以及在剩余的映射缩小循环期间使用数据结构，其中剩余的映射缩小轮不在节点之间发送消息。 该方法还可以包括将节点的集群分配存储在存储器中。
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Patent Agency Ranking
公开(公告)号：US20150220530A1
公开(公告)日：2015-08-06
申请号：US14278811
申请日：2014-05-15
Applicant: GOOGLE INC.
Inventor： Seyed Vahab Mirrokni Banadaki , Silvio Lattanzi , Jonathan Ezra Feldman , Alessandro Epasto , Stefano Leonardi , Hugh Lynch , Varun Sharma
IPC: G06F17/30
CPC classification number: G06F17/30943 , G06F2216/03 , G06Q30/0241
Abstract: Systems and methods offer an efficient approach to computing similarity rankings in bipartite graphs. An example system includes at least one processor and memory storing a bipartite graph having a first set and a second set of nodes, with nodes in the first set being connected to nodes in the second set by edges. The memory also stores instructions that, when executed by the at least one processor, cause the system to assign each node in the second set to one of a plurality of categories and, for each of the plurality of categories, generate a subgraph. The subgraph comprises of a subset of nodes in the first set and edges linking the nodes in the subset, where the nodes in the subset are selected based on connection to a node in the second set that is assigned to the category. The system uses the subgraph to respond to queries.
Abstract translation: 系统和方法提供了一种有效的方法来计算二分图中的相似性排名。 示例系统包括至少一个处理器和存储具有第一组和第二组节点的二分图的存储器，其中第一组中的节点通过边缘连接到第二组中的节点。 存储器还存储指令，当由至少一个处理器执行时，使得系统将第二组中的每个节点分配给多个类别中的一个，并且对于多个类别中的每一个分类，生成子图。 子图包括第一组中的节点的子集和链接子集中的节点的边缘，其中基于与分配给该类别的第二集合中的节点的连接来选择子集中的节点。 系统使用子图来回应查询。
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公开(公告)号：US20150006606A1
公开(公告)日：2015-01-01
申请号：US14145127
申请日：2013-12-31
Applicant: GOOGLE INC.
Inventor： Eduardo Madeira Fleury , Seyed Vahab Mirrokni Banadaki , Nissan Hajaj , Jerry Yi Ding , Silvio Lattanzi
IPC: H04L29/08
CPC classification number: G06F17/30958 , G06F9/546 , G06F2209/548 , G06Q10/06
Abstract: Systems and methods for sending asynchronous messages include receiving, using at least one processor, at a node in a distributed graph, a message with a first value and determining, at the node, that the first value replaces a current value for the node. In response to determining that the first value replaces the current value, the method also includes setting a status of the node to active and sending messages including the first value to neighboring nodes. The method may also include receiving the messages to the neighboring nodes at a priority queue. The priority queue propagates messages in an intelligently asynchronous manner, and the priority queue propagates the messages to the neighboring nodes, the status of the node is set to inactive. The first value may be a cluster identifier or a shortest path identifier.
Abstract translation: 用于发送异步消息的系统和方法包括：使用至少一个处理器在分布式图中的节点处接收具有第一值的消息，并在该节点处确定第一值替换该节点的当前值。 响应于确定第一值替换当前值，该方法还包括将节点的状态设置为活动，并将包括第一值的消息发送到相邻节点。 该方法还可以包括在优先级队列处接收消息到相邻节点。 优先级队列以智能异步方式传播消息，优先级队列将消息传播到相邻节点，节点的状态设置为非活动状态。 第一个值可以是集群标识符或最短路径标识符。
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公开(公告)号：US09852230B2
公开(公告)日：2017-12-26
申请号：US14145127
申请日：2013-12-31
Applicant: GOOGLE INC.
Inventor： Eduardo Madeira Fleury , Seyed Vahab Mirrokni Banadaki , Nissan Hajaj , Jerry Yi Ding , Silvio Lattanzi
CPC classification number: G06F17/30958 , G06F9/546 , G06F2209/548 , G06Q10/06
Abstract: Systems and methods for sending asynchronous messages include receiving, using at least one processor, at a node in a distributed graph, a message with a first value and determining, at the node, that the first value replaces a current value for the node. In response to determining that the first value replaces the current value, the method also includes setting a status of the node to active and sending messages including the first value to neighboring nodes. The method may also include receiving the messages to the neighboring nodes at a priority queue. The priority queue propagates messages in an intelligently asynchronous manner, and the priority queue propagates the messages to the neighboring nodes, the status of the node is set to inactive. The first value may be a cluster identifier or a shortest path identifier.
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公开(公告)号：US09760619B1
公开(公告)日：2017-09-12
申请号：US14279200
申请日：2014-05-15
Applicant: Google Inc.
Inventor： Silvio Lattanzi , Stefano Leonardi
CPC classification number: G06F17/30598 , G06F17/30958 , G06Q50/01
Abstract: The disclosure includes a system and method for generating weighted clustering coefficients for a social network graph. The system includes a processor and a memory storing instructions that when executed cause the system to: receive social graph data associated with a social network, the social graph data including nodes, edges that connect the nodes and weights associated with the edges in a social graph, determine a first probability of existence of an edge in the social graph based on the weights, determine a second probability that a first node forms a triangle with two neighbor nodes, and compute a weighted clustering coefficient for the first node based on the first and second probabilities.
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公开(公告)号：US20150006619A1
公开(公告)日：2015-01-01
申请号：US14143894
申请日：2013-12-30
Applicant: GOOGLE INC.
Inventor： Seyed Vahab Mirrokni Banadaki , Raimondas Kiveris , Vibhor Rastogi , Silvio Lattanzi , Sergei Vassilvitskii
IPC: H04L29/08
CPC classification number: H04L67/10 , G06F9/5066 , G06F9/546 , G06Q10/06
Abstract: Systems and methods for improving the time and cost to calculate connected components in a distributed graph are disclosed. One method includes reducing a quantity of map-reduce rounds used to determine a cluster assignment for a node in a large distributed graph by alternating between two hashing functions in the map stage of a map-reduce round and storing the cluster assignment for the node in a memory. Another method includes reducing a quantity of messages sent during map-reduce rounds by performing a predetermined quantity of rounds to generate, for each node, a set of potential cluster assignments, generating a data structure in memory to store a mapping between each node and its potential cluster assignment, and using the data structure during remaining map-reduce rounds, wherein the remaining map-reduce rounds do not send messages between nodes. The method can also include storing the cluster assignment for the node in a memory.
Abstract translation: 公开了用于改善计算分布图中的连接部件的时间和成本的系统和方法。 一种方法包括通过在map-reduce round的映射阶段中的两个散列函数之间交替并且将节点的集群分配存储在减少用于确定大分布式图中的节点的集群分配的地图缩小轮数量 一个记忆 另一种方法包括通过执行预定量的轮次来减少在地图缩小轮期间发送的消息的数量，以为每个节点生成一组潜在的分组分配，在存储器中生成数据结构以存储每个节点与其之间的映射 潜在的集群分配，以及在剩余的映射缩小循环期间使用数据结构，其中剩余的映射缩小轮不在节点之间发送消息。 该方法还可以包括将节点的集群分配存储在存储器中。
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