• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.571-573
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• 2009

Mobile Ad-hoc Network(MANET) needs efficient node management because the wireless network has energy constraints. 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. Previously proposed a hybrid routing CACH prolong the network lifetime and decrease latency. However the algorithm has a problem when node density is increase. In this paper, we propose a new method that the CACHE(Context-aware Clustering Hierarchy and Energy efficient) algorithm. The proposed analysis could not only help in defining the optimum depth of hierarchy architecture CACH utilize, but also improve the problem about node density.

• Journal of KIISE:Software and Applications
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• v.37 no.3
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• pp.214-221
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• 2010

The search-results clustering problem is defined as the automatic and on-line grouping of similar documents in search results returned from a search engine. In this paper, we propose a new search-results clustering algorithm specialized for a paper search service. Our system consists of two algorithmic phases: Category Hierarchy Generation System (CHGS) and Paper Clustering System (PCS). In CHGS, we first build up the category hierarchy, called the Field Thesaurus, for each research field using an existing research category hierarchy (KOSEF's research category hierarchy) and the keyword expansion of the field thesaurus by a word clustering method using the K-means algorithm. Then, in PCS, the proposed algorithm determines the category of each paper using top-down and bottom-up methods. The proposed system can be used in the application areas for retrieval services in a specialized field such as a paper search service.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.277-280
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• 2009

Mobile Ad-hoc Network(MANET) 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 that 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.

• KIISE Transactions on Computing Practices
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• v.21 no.6
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• pp.436-441
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• 2015

There are many types of clustering algorithms such as centroid, hierarchical, or density-based methods. Each algorithm has unique data grouping principles, which creates different varieties of clusters. Ordering Points To Identify the Clustering Structure (OPTICS) is a well-known density-based algorithm to analyze arbitrary shaped and varying density clusters, but the obtained clusters only correlate loosely. Hierarchical agglomerative clustering (HAC) reveals a hierarchical structure of clusters, but is unable to clearly find non-convex shaped clusters. In this paper, we provide a novel hierarchy generation framework and application which can aid users by combining the advantages of the two clustering methods.

• Journal of the Korea Society for Simulation
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• v.21 no.4
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• pp.47-56
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• 2012

In this study, we use a parallel simulator PASENS(Parallel SEnsor Network Simulator) to predict power consumption and data reception rate of the hierarchical routing protocols for sensor network - LEACH (Low-Energy Adaptive Clustering Hierarchy), TL-LEACH (Two Level Low-Energy Adaptive Clustering Hierarchy), M-LEACH (Multi hop Low-Energy Adaptive Clustering Hierarchy) and LEACH-C (LEACH-Centralized). According to simulation results, M-LEACH routing protocol shows the highest data reception rate for the wider area, since more sensor nodes are involved in the data transmission. And LEACH-C routing protocol, where the sink node considers the entire node's residual energy and location to determine the cluster head, results in the most efficient energy consumption and in the narrow area needed long life of sensor network.

• Korean Management Science Review
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• v.24 no.2
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• pp.57-72
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• 2007

Many Applications of scientific research have coupled with functional data signal clustering techniques to discover novel characteristics that can be used for the diagnoses of several issues. In this article we present an interpretable multi-scale cluster hierarchy framework for clustering functional data using its multi-aspect frequency information. The suggested method focuses on how to effectively select transformed features/variables in unsupervised manner so that finally reduce the data dimension and achieve the multi-purposed clustering. Specially, we apply our suggested method to mutual fund returns and make superior-performing funds group based on different aspects such as global patterns, seasonal variations, levels of noise, and their combinations. To promise our method producing a quality cluster hierarchy, we give some empirical results under the simulation study and a set of real life data. This research will contribute to financial market analysis and flexibly fit to other research fields with clustering purposes.

• 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.

• The Journal of Society for e-Business Studies
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• v.16 no.4
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• pp.301-319
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• 2011

Blog plays an important role as new type of knowledge base distinguishing from traditional web resource. While information resources in their existing website dealt with a wide range of topics, information resources of the blog are concentrated in specific units of information depending on the user's interests and have the criteria of classification forresources published by tagging. In this research, we build a tag hierarchy utilizing title keywords and tags of the blog, and propose apost clustering methodology applying the tag hierarchy. We then generate the tag hierarchy reflected the relationship between tags and develop the tag clustering methodology according to tag similarity. In this paper, we analyze the possibility of applying the proposed methodology with real-world examples and evaluate its performances through developed prototype system.

• Proceedings of the CALSEC Conference
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• 2004.02a
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• pp.294-301
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• 2004

·Text-mining approach to e-documents organization based on topic hierarchy - Machine-Learning ＆ information Theory-based ㆍ 'Category(topic) discovery' problem → document bundle-based user-constraint document clustering ㆍ 'Automatic categorization' problem → Accelerated EM with CU-based active learning → 'Hierarchy Construction' problem → Unsupervised learning of category subsumption relation