• Title/Summary/Keyword: cluster hierarchy depth

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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.

CACH Distributed Clustering Protocol Based on Context-aware (CACH에 의한 상황인식 기반의 분산 클러스터링 기법)

  • Mun, Chang-Min;Lee, Kang-Whan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.6
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    • pp.1222-1227
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    • 2009
  • In this paper, we proposed a new method, the CACH(Context-aware Clustering Hierarchy) algorithm in Mobile Ad-hoc Network(MANET) systems. The proposed CACH algorithm based on hybrid and clustering protocol that provide the reliable monitoring and control of a variety of environments for remote place. To improve the routing protocol in MANET, energy efficient routing protocol would be required as well as considering the mobility would be needed. The proposed analysis could help in defining the optimum depth of hierarchy architecture CACH utilize. Also, the proposed CACH could be used localized condition to enable adaptation and robustness for dynamic network topology protocol and this provide that our hierarchy to be resilient. As a result, our simulation results would show that a new method for CACH could find energy efficient depth of hierarchy of a cluster.

Clustering Ad hoc Network Scheme and Classifications Based on Context-aware

  • Mun, Chang-Min;Lee, Kang-Whan
    • Journal of information and communication convergence engineering
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    • v.7 no.4
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    • pp.475-479
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    • 2009
  • In ad hoc network, the scarce energy management of the mobile devices has become a critical issue in order to extend the network lifetime. Current research activity for the Minimum Energy Multicast (MEM) problem has been focused on devising efficient centralized greedy algorithms for static ad hoc networks. In this paper, we consider mobile ad hoc networks(MANETs) that could provide the reliable monitoring and control of a variety of environments for remote place. Mobility of MANET would require the topology change frequently compared with a static network. To improve the routing protocol in MANET, energy efficient routing protocol would be required as well as considering the mobility would be needed. In this paper, we propose a new method, the CACH(Context-aware Clustering Hierarchy) algorithm, a hybrid and clustering-based protocol that could analyze the link cost from a source node to a destination node. The proposed analysis could help in defining the optimum depth of hierarchy architecture CACH utilize. The proposed CACH could use localized condition to enable adaptation and robustness for dynamic network topology protocol and this provide that our hierarchy to be resilient. As a result, our simulation results would show that CACH could find energy efficient depth of hierarchy of a cluster.

A Study on Cluster Hierarchy Depth in Hierarchical Clustering (계층적 클러스터링에서 분류 계층 깊이에 관한 연구)

  • Jin, Hai-Nan;Lee, Shin-won;An, Dong-Un;Chung, Sung-Jong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2004.05a
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    • pp.673-676
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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. In particular, hierarchical clustering provide a view of the data at different levels, making the large document collections are adapted to people's instinctive and interested requires. Many papers have shown that the hierarchical clustering method takes good-performance, but is limited because of its quadratic time complexity. In contrast, K-means has a time complexity that is linear in the number of documents, but is thought to produce inferior clusters. Think of the factor of simpleness, high-quality and high-efficiency, we combine the two approaches providing a new system named CONDOR system [10] with hierarchical structure based on document clustering using K-means algorithm to "get the best of both worlds". The performance of CONDOR system is compared with the VIVISIMO hierarchical clustering system [9], and performance is analyzed on feature words selection of specific topics and the optimum hierarchy depth.

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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 context-aware and Energy Efficient Routing Protocol for Mobile Ad-hoc Network (상황인식 기반의 에너지 효율적인 경로 설정 기법 연구)

  • Mun, Chang-Min;Lee, Kang-Whan
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2010.10a
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    • pp.377-380
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    • 2010
  • MANET(Mobile Ad-hoc Network) has been proposed as a infrastructure-less network using distributed algorithm for remote environment monitoring and control. The mobility of MANET would make the topology change frequently compared with a static network and a node is resource-constrained. Hence, to improve the routing protocol in MANET, energy efficient routing protocol is required as well as considering the mobility would be needed. In this paper, we extend RODMRP(Resilient Ontology-based Dynamic Multicast Routing Protocol) structure by a modifying the level of cluster. We call this network protocol CACH-RODMRP. Our contribution consists estimating the optimal level of clustering depth with considering node position and reducing the network residual energy. The simulation results of proposal algorithm show that the energy is significantly reduced compared with the previous clustering based routing algorithm for the MANET.

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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.