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By Robert Grossman, Yike Guo, R.L. Grossman

High functionality info Mining: Scaling Algorithms, functions andSystems brings jointly in a single position very important contributions and up to date study ends up in this fast-paced sector.
High functionality information Mining: Scaling Algorithms, purposes andSystems serves as an exceptional reference, delivering perception into probably the most hard examine concerns within the field.

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Otherwise, the current cluster may need to be merged with another cluster (see Lemmas 5 and 7). At the end of the expansion, 0& will be appended to / The retrieval of the (SV neighborhood for a given object is performed by using a region query. , this region is a circle. The center of this circle is the query object and the radius equals Eps. Obviously, the run-time of PartDBSCAN is run-time of a region query): for every point in the partition 6 a region query is performed by using the dR*-tree.

We implemented our method on a number of workstations connected via Ethernet (10 Mbit). A performance evaluation shows that PDBSCAN scales up very well and has excellent speedup and sizeup behavior. g. classification and trend detection. This paper is organized as follows. Section 2 surveys previous efforts to parallelize other clustering algorithms. Section 3 briefly describes the algorithm DBSCAN and Section 4 presents our parallel clustering algorithm PDBSCAN. Section 5 shows experimental results and evaluates our parallel algorithm with respect to speedup, scalability, and sizeup.

The query processing on a dR*-tree is very similar to the query processing on an R*-tree: a query is performed by starting at the root and computing all entries whose rectangle qualifies. For these entries, the corresponding child nodes are read into the main memory and the query process is repeated, unless the )LJXUH Distributed spatial index. 38 A FAST PARALLEL CLUSTERING ALGORITHM 273 node in question is a leaf node. If the qualifying node is a local node, then this node can be read into the main memory.

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