Spatial Cluster Analysis by the Bin-Packing Problem and DNA Computing Technique
Spatial cluster analysis is an important data mining task. Typical techniques include CLARANS, density- and gravity-based clustering, and other algorithms based on traditional von Neumann's computing architecture. The purpose of this paper is to propose a technique for spatial cluster analysis...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2013-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2013/891428 |
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| Summary: | Spatial cluster analysis is an important data mining task. Typical
techniques include CLARANS, density- and gravity-based clustering,
and other algorithms based on traditional von Neumann's computing
architecture. The purpose of this paper is to propose a technique
for spatial cluster analysis based on sticker systems of DNA
computing. We will adopt the Bin-Packing Problem idea and then
design algorithms of sticker programming. The proposed technique
has a better time complexity. In the case when only the
intracluster dissimilarity is taken into account, this time
complexity is polynomial in the amount of data points, which
reduces the NP-completeness nature of spatial cluster analysis.
The new technique provides an alternative method for traditional
cluster analysis. |
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| ISSN: | 1026-0226 1607-887X |