Paypal, Inc.

Zhenyu Qiao

Jie Huang

Jun Gu

Yunjing Dai

Si Feng

Methods and systems are presented for detecting groups within a graph using computer-based multi-threading techniques. These techniques provide technical improvements in computing power and efficiency for analysis of large graphs. A group detection system accesses a graph. Threads are instantiated to perform task related to a group detection process based on the nodes in the graph, where a thread is instantiated for a corresponding node. Each thread determines a neighbor count representing a number of neighbor nodes having one degree of separation from the corresponding node. Each thread also generates a list comprising an identity of the corresponding node and identities of the neighbor nodes. The thread transmits the list only to threads corresponding to a first subset of the neighbor nodes having more neighbors than the corresponding node, but not to threads corresponding to a second subset of the neighbor nodes having less neighbors than the corresponding nodes.

Graph-based multi-threading group detection

Methods and systems are presented for retrieving data associated with one or more portions of a graph by a computer system. Multiple graph indices are generated based on the graph. Each of the multiple graph indices stores records of data representing the graph in different formats. Upon receiving a request for accessing a sub-graph of the graph, edge-based attributes of the sub-graph are analyzed. The sub-graph may be divided into a first portion and a second portion of the sub-graph. A first graph index may be selected for retrieving records associated with the first portion of the sub-graph based on the edge-based attributes of the first portion of the sub-graph. A second graph index may be selected for retrieving records associated with the second portion of the sub-graph based on the edge-based attributes of the second portion of the sub-graph.

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Shanghai, China

Zhenyu Qiao