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Data stream mining has gained growing attentions recently. Concept drift is a particular problem in data stream mining, which is defined as the distribution of data may change over time. Most of current methods try to estimate the current distribution or reconstruct the current distribution from a mixture of old distributions. They suffer problems of estimation and reconstruction error respectively...
In this paper, we study the problem of filtering and querying massive XML data against a large set of XPath patterns in Univariate XPath. Based on an efficient matching engine XSIGMA for linear XPath patterns with Boolean expression over keywords and a twig evaluator over event streams, we propose an XPath filtering/querying engine Chimera, which runs fast and stably for any XPath patterns without...
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