Graph Mining on Streams
Graph Mining on Streams
复制标题
流上的图挖掘
DOI：
10.1007/978-0-387-39940-9_184
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
A. Mcgregor
中科院分区：
文献类型：
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作者：
A. Mcgregor
多通道模型：在图挖掘中，考虑可能需要多个通过流的算法，这很常见。 W-Stream模型也有工作，其中允许算法在每个通过期间写入流[9]。然后，这些注释可以在连续通过期间被算法利用，并且可以证明，这为要模拟的PRAM算法的模型赋予了足够的功能[8]。流式模型更进一步，并允许对通过注释[1]编码的密钥对数据流进行分类。
Multi-Pass Models: It is common in graph mining to consider algorithms that may take more than one pass over the stream. There has also been work in the W-Stream model in which the algorithm is allowed to write to the stream during each pass [9]. These annotations can then be utilized by the algorithm during successive passes and it can be shown that this gives sufficient power to the model for PRAM algorithms to be simulated [8]. The Stream-Sort model goes one step further and allows sorting passes in which the data stream is sorted according to a key encoded by the annotations [1].