• Title/Summary/Keyword: 클러스터 계층 깊이

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Selection of Cluster Hierarchy Depth and Initial Centroids in Hierarchical Clustering using K-Means Algorithm (K-Means 알고리즘을 이용한 계층적 클러스터링에서 클러스터 계층 깊이와 초기값 선정)

  • Lee, Shin-Won;An, Dong-Un;Chong, Sung-Jong
    • Journal of the Korean Society for information Management
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    • v.21 no.4 s.54
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    • pp.173-185
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    • 2004
  • Fast and high-quality document clustering algorithms play an important role in providing data exploration by organizing large amounts of information into a small number of meaningful clusters. Many papers have shown that the hierarchical clustering method takes good-performance, but is limited because of its quadratic time complexity. In contrast, with a large number of variables, K-means has a time complexity that is linear in the number of documents, but is thought to produce inferior clusters. In this paper, Condor system using K-Means algorithm Compares with regular method that the initial centroids have been established in advance, our method performance has been improved a lot.

Selection of Cluster Hierarchy Depth in Hierarchical Clustering using K-Means Algorithm (K-means 알고리즘을 이용한 계층적 클러스터링에서의 클러스터 계층 깊이 선택)

  • Lee, Won-Hee;Lee, Shin-Won;Chung, Sung-Jong;An, Dong-Un
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.45 no.2
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    • pp.150-156
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    • 2008
  • Many papers have shown that the hierarchical clustering method takes good-performance, but is limited because of its quadratic time complexity. In contrast, with a large number of variables, K-means reduces a time complexity. Think of the factor of simplify, high-quality and high-efficiency, we combine the two approaches providing a new system named CONDOR system with hierarchical structure based on document clustering using K-means algorithm. Evaluated the performance on different hierarchy depth and initial uncertain centroid number based on variational relative document amount correspond to given queries. Comparing with regular method that the initial centroids have been established in advance, our method performance has been improved a lot.

A Study on Energy Conservative Hierarchical Clustering for Ad-hoc Network (애드-혹 네트워크에서의 에너지 보존적인 계층 클러스터링에 관한 연구)

  • Mun, Chang-Min;Lee, Kang-Whan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.12
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    • pp.2800-2807
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    • 2012
  • An ad-hoc wireless network provides self-organizing data networking while they are routing of packets among themselves. Typically multi-hop and control packets overhead affects the change of route of transmission. There are numerous routing protocols have been developed for ad hoc wireless networks as the size of the network scale. Hence the scalable routing protocol would be needed for energy efficient various network routing environment conditions. The number of depth or layer of hierarchical clustering nodes are analyzed the different clustering structure with topology in this paper. To estimate the energy efficient number of cluster layer and energy dissipation are studied based on distributed homogeneous spatial Poisson process with context-awareness nodes condition. The simulation results show that CACHE-R could be conserved the energy of node under the setting the optimal layer given parameters.