Discovering Application Level Semantics for Data Compression Using HCT

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Provided by: International Journal of Innovative Technology and Exploring Engineering (IJITEE)
Topic: Big Data
Format: PDF
Natural phenomena show that many creatures form large social groups and move in regular patterns. However, previous papers focus on finding the movement patterns of each single object or all objects. The author propose an efficient distributed mining algorithm to jointly identify a group of moving objects and discover their movement patterns in wireless sensor networks. This algorithm consists of the local mining phase and the cluster ensembling phase. The local mining phase adopts the VMM model together with probabilistic suffix tree to find the moving patterns, as well as highly connected component to partition the moving objects.
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