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    • 33. 发明授权
    • Large graph measurement
    • 大图测量
    • US08583667B2
    • 2013-11-12
    • US13314555
    • 2011-12-08
    • Sreenivas Gollapudi
    • Sreenivas Gollapudi
    • G06F17/30G06F7/00
    • 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。
    • 37. 发明申请
    • SYSTEM OF RANKING SEARCH RESULTS BASED ON QUERY SPECIFIC POSITION BIAS
    • 基于查询特定位置偏移的搜索结果排序系统
    • US20100153370A1
    • 2010-06-17
    • US12335396
    • 2008-12-15
    • Sreenivas GollapudiRina Panigrahy
    • Sreenivas GollapudiRina Panigrahy
    • G06F17/30
    • G06F16/958
    • A model based on a generalization of the Examination Hypothesis is disclosed that states that for a given query, the user click probability on a document in a given position is proportional to the relevance of the document and a query specific position bias. Based on this model the relevance and position bias parameters are learned for different queries and documents. This is done by translating the model into a system of linear equations that can be solved to obtain the best fit relevance and position bias values. A cumulative analysis of the position bias curves may be performed for different queries to understand the nature of these curves for navigational and informational queries. In particular, the position bias parameter values may be computed for a large number of queries. Such an exercise reveals whether the query is informational or navigational. A method is also proposed to solve the problem of dealing with sparse click data by inferring the goodness of unclicked documents for a given query from the clicks associated with similar queries.
    • 披露了基于考试假设泛化的模型,其中指出,对于给定查询,给定位置上的文档上的用户点击概率与文档的相关性和查询特定位置偏差成比例。 基于此模型,针对不同的查询和文档学习相关性和位置偏差参数。 这是通过将模型转换成可以解决以获得最佳拟合相关性和位置偏差值的线性方程组的系统来完成的。 可以对不同的查询执行位置偏差曲线的累积分析,以了解导航和信息查询的这些曲线的性质。 特别地,可以针对大量查询来计算位置偏差参数值。 这样的练习揭示了查询是信息还是导航。 还提出了一种通过从与类似查询相关联的点击推断给定查询的未点击文档的良好性来解决处理稀疏点击数据的问题的方法。