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    • 61. 发明申请
    • METHOD OF FINDING CANDIDATE SUB-QUERIES FROM LONGER QUERIES
    • 从长期查询中查找候选子问题的方法
    • US20090089266A1
    • 2009-04-02
    • US11863045
    • 2007-09-27
    • Sreenivas GollapudiRina Panigrahy
    • Sreenivas GollapudiRina Panigrahy
    • G06F17/30
    • G06F17/30693G06F17/30457
    • A method is disclosed for identifying queries stored in a log which are semantically related to an input query that may include a large number of terms. A set of one or more subsequences are generated for each query stored in the log, and these sets of subsequences are stored in a lookup table. A set of one or more subsequences are also generated for the input query. The subsequences in the lookup table and of the input query are generated by hashing of the respective query terms to a value between 0 and 1 using a known technique of min-hashing. The present system then constructs the subsequences of the query using the k-min hashes of the query, where k is an integer based on the number of terms in the query.
    • 公开了一种用于识别存储在日志中的查询与可能包括大量项目的输入查询语义相关的查询的方法。 为存储在日志中的每个查询生成一组或多个子序列,并将这些子序列存储在查找表中。 还为输入查询生成一组或多个子序列。 查询表和输入查询中的子序列通过使用最小哈希算法的已知技术将相应的查询项散列为0到1之间的值来生成。 本系统然后使用查询的k-min哈希构建查询的子序列,其中k是基于查询中的项数的整数。
    • 64. 发明申请
    • BID DISCOUNTING USING EXTERNALITIES
    • 使用外来物品折价
    • US20130226713A1
    • 2013-08-29
    • US13407739
    • 2012-02-28
    • Sreenivas GollapudiAnand Bhalgat
    • Sreenivas GollapudiAnand Bhalgat
    • G06Q30/02G06Q30/08
    • G06Q30/02G06Q30/08
    • Advertisers provide bids for the placement of one or more advertisements on web pages, along with a set of externalities. The externalities from an advertiser indicate discounts that can be applied to their bid based on information learned from a browse history of a user. The externalities may include externalities based on previous viewings of advertisements from the advertiser by the user, externalities based on previous viewings of advertisements from competitor advertisers viewed by the user, and externalities based on web pages or domains that have been visited by the user. When a request for an advertisement is received, the externalities are used to discount the provided bids based on the browse history of the user. An advertisement is then selected based on the discounted bids.
    • 广告商提供在网页上放置一个或多个广告的出价以及一组外部性。 来自广告商的外部性表示可以根据从用户的浏览历史获得的信息来应用于其出价的折扣。 外部性可以包括基于用户先前对广告商的广告的观察的外部性,基于用户观看的来自竞争者广告商的广告的先前观看的外部性以及基于用户访问过的网页或域的外部性。 当接收到广告请求时,根据用户的浏览历史使用外部性来折扣提供的出价。 然后根据折扣出价选择广告。
    • 66. 发明申请
    • FULFILLING QUERIES USING SPECIFIED AND UNSPECIFIED ATTRIBUTES
    • 使用指定和未经验证的属性的丰富的查询
    • US20120226679A1
    • 2012-09-06
    • US13038409
    • 2011-03-02
    • Sreenivas GollapudiSayan Bhattacharya
    • Sreenivas GollapudiSayan Bhattacharya
    • G06F17/30
    • G06F17/30958
    • A query is received and processed to determine one or more specified and unspecified attributes in the query. The specified and unspecified attributes may correspond to attributes of one or more items. A graph is generated for the items and includes a node for each item and an edge between each unique pair of nodes. Each node is assigned a cost based on a distance between the specified attributes of the query and the attributes of the item associated with the node. Each edge is assigned a weight based on a distance between the unspecified attributes associated with the nodes of the node pair corresponding to the edge. A set of nodes from the graph is selected by minimizing a total cost of the nodes while maximizing a dispersion of the nodes based on the edge weights.
    • 接收并处理查询以确定查询中的一个或多个指定和未指定的属性。 指定和未指定的属性可以对应于一个或多个项目的属性。 为项目生成图形,并包括每个项目的节点和每个唯一的节点对之间的边。 根据查询的指定属性与与节点相关联的项目的属性之间的距离,为每个节点分配一个成本。 基于与边缘对应的节点对的节点相关联的未指定属性之间的距离,为每个边缘分配权重。 通过最小化节点的总成本,同时基于边缘权重最大化节点的色散来选择来自图形的一组节点。
    • 67. 发明申请
    • LARGE GRAPH MEASUREMENT
    • 大图测量
    • US20120078927A1
    • 2012-03-29
    • US13314555
    • 2011-12-08
    • Sreenivas Gollapudi
    • Sreenivas Gollapudi
    • G06F17/30
    • G06F17/30876G06F17/30873
    • As provided herein, a pairwise distance between nodes in a large graph can be determined efficiently. URL-sketches are generated for respective nodes in an index by extracting labels from respective nodes, which provide a reference to a link between the nodes, aggregating the labels into sets for respective nodes, and storing the sets of labels as URL-sketches. Neighborhood-sketches are generated for the respective nodes in the index using the URL-sketches, by determining a neighborhood for a node and generating a sketch using labels that are associated with the respective neighboring nodes. A distance between two nodes is determined by computing an approximate number of paths and an approximate path length between the two nodes, using the neighborhood sketches for the two nodes.
    • 如本文所提供的,可以有效地确定大图中的节点之间的成对距离。 通过从相应节点提取标签,提供对节点之间的链接的引用,将标签聚集到各个节点的集合中,并将标签集合存储为URL草图,从而为索引中的相应节点生成URL草图。 通过使用URL草图,通过确定节点的邻域并使用与各个相邻节点相关联的标签生成草图来为索引中的相应节点生成邻域草图。 通过使用两个节点的邻域草图计算两个节点之间的近似路径数和两个节点之间的近似路径长度来确定两个节点之间的距离。
    • 68. 发明申请
    • DETERMINING QUERY INTENT
    • 确定查询内容
    • US20110314012A1
    • 2011-12-22
    • US12816389
    • 2010-06-16
    • Krishnaram N. G. KenthapadiPanayiotis TsaparasSreenivas GollapudiRakesh Agrawal
    • Krishnaram N. G. KenthapadiPanayiotis TsaparasSreenivas GollapudiRakesh Agrawal
    • G06F17/30
    • G06F17/30979
    • A tree structure has a node associated with each category of a hierarchy of item categories. Child nodes of the tree are associated with sub-categories of the categories associated with parent nodes. Training data including received queries and indicators of a selected item category for each received query is combined with the tree structure by associating each query with the node corresponding to the selected category of the query. When a query is received, a classifier is applied to the nodes to generate a probability that the query is intended to match an item of the category associated with the node. The classifier is applied until the probability is below a threshold. One or more categories associated with the nodes that are closest to the intent of the received query are selected and indicators of items of those categories that match the received query are output.
    • 树结构具有与项目类别的层次结构的每个类别相关联的节点。 树的子节点与与父节点相关联的类别的子类别相关联。 通过将每个查询与对应于所选择的查询类别的节点相关联,将包括接收到的查询和针对每个接收到的查询的所选项目类别的指示符的训练数据与树结构组合。 当接收到查询时,分类器被应用于节点以产生查询旨在匹配与节点相关联的类别的项目的概率。 应用分类器直到概率低于阈值。 选择与接收到的查询的意图最接近的节点相关联的一个或多个类别,并输出与接收到的查询匹配的那些类别的项目的指示符。
    • 70. 发明申请
    • LEARNING DIVERSE RANKINGS OVER DOCUMENT COLLECTIONS
    • 学习文档集合中的多样性排名
    • US20110264639A1
    • 2011-10-27
    • US12764112
    • 2010-04-21
    • Aleksandrs SlivkinsSreenivas GollapudiFilip Radlinski
    • Aleksandrs SlivkinsSreenivas GollapudiFilip Radlinski
    • G06F17/30
    • G06F16/9535
    • A document selector selects and ranks documents that are relevant to a query. The document selector executes an instance of a multi-armed bandits algorithm to select a document for each slot of a results page according to one or more strategies. The documents are selected in an order defined by the results page and documents selected for previous slots are used to guide the selection of a document for a current slot. If a document in a slot is subsequently selected, the strategy used to select the document is rewarded with positive feedback. When the uncertainty in an estimate of the utility of a strategy is less than the variation between documents associated with the strategy, the strategy is subdivided into multiple strategies. The document selector is able to “zoom in” on effective strategies and provide more relevant search results.
    • 文档选择器选择和排序与查询相关的文档。 文档选择器执行多武装强盗算法的实例,以根据一个或多个策略为结果页面的每个时隙选择文档。 文档按照结果页面定义的顺序进行选择,为先前的插槽选择的文档用于指导当前插槽文档的选择。 如果随后选择了插槽中的文档,则用于选择文档的策略将获得积极的反馈。 当战略效用估计的不确定性低于与战略相关的文件之间的变化时,该策略被细分为多种策略。 文档选择器能够“放大”有效策略并提供更相关的搜索结果。