用于高质量聚类的流数据算法

Liadan O'Callaghan, A. Meyerson, R. Motwani, Nina Mishra, S. Guha
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引用次数: 681

摘要

流数据分析最近在许多应用中引起了人们的注意,包括电话记录、网络文档和点击流。对于这种分析,消耗少量内存的单遍算法至关重要。我们描述了一种有效聚类大数据流的流算法。我们还提供了该算法在合成数据流和真实数据流上的性能的经验证据。
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Streaming-data algorithms for high-quality clustering
Streaming data analysis has recently attracted attention in numerous applications including telephone records, Web documents and click streams. For such analysis, single-pass algorithms that consume a small amount of memory are critical. We describe such a streaming algorithm that effectively clusters large data streams. We also provide empirical evidence of the algorithm's performance on synthetic and real data streams.
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