Titlebook: Data Streams; Models and Algorithm Charu C. Aggarwal Book 2007 Springer-Verlag US 2007 algorithm.algorithms.data.data streams.database.freq

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書目名稱Data Streams影響因子(影響力)




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A Survey of Classification Methods in Data Streams,to as data streams. Streaming data is ubiquitous today and it is often a challenging task to store, analyze and visualize such rapid large volumes of data. Most conventional data mining techniques have to be adapted to run in a streaming environment, because of the underlying resource constraints in

caldron

Frequent Pattern Mining in Data Streams, data streams have attracted a lot of research interests. Compared with other streaming queries, frequent pattern mining poses great challenges due to high memory and computational costs, and accuracy requirement of the mining results..In this chapter, we overview the state-of-art techniques to mine

Amenable

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Multi-Dimensional Analysis of Data Streams Using Stream Cubes,ant characteristic: .. To discover high-level dynamic and evolving characteristics, one may need to perform multi-level, multi-dimensional on-line analytical processing (OLAP) of stream data. Such necessity calls for the investigation of new architectures that may facilitate on-line analytical proce

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Fluctuate

The Sliding-Window Computation Model and Results,l and pertinent than older data. In such cases, we would like to answer questions about the data only over the last . most recent data elements (. is a parameter). We formalize this model of computation and answer questions about how much space and computation time is required to solve certain probl

ADORE

A Survey of Synopsis Construction in Data Streams,ining algorithms require efficient execution which can be difficult to achieve with a fast data stream. In many cases, it may be acceptable to generate . for such problems. In recent years a number of . have been developed, which can be used in conjunction with a variety of mining and query processi

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