• Title/Summary/Keyword: 이슈 클러스터링

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Efficient Cluster Head Selection Technique (효율적인 클러스터 헤드 선출기법)

  • Park Soomin;Nam Choonsung;Kim Kyeongmin;Shin Yongtae
    • Proceedings of the Korean Information Science Society Conference
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    • 2005.11a
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    • pp.496-498
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    • 2005
  • 수많은 센서들로 이루어진 센서 네트워크에서는 노드의 제한된 에너지로 인해, 에너지 효율적 사용이 중요한 이슈이다. 따라서 에너지 효율적인 라우팅을 위하여 많은 알고리즘이 연구되고 있다. 이들 알고리즘들 중 클러스터링 기법은 센서 노드가 싱크와 직접 통신하는 방법이 아닌 클러스터 헤드로 선출된 노드와 통신하여 클러스터 헤드가 센싱된 정보를 모아 싱크에 보냄으로써 에너지 소비를 줄이게 된다. 이 기법은 클러스터 헤드 선정이 무엇보다도 중요한 이슈이다. 따라서 이 논문에서는 잔존 에너지의 양과 노드의 상대적 위치에 따라 클러스터 헤드를 선출함으로써 에너지 효율을 최적화 시킬 수 있는 기법을 제안한다.

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비트코인 익명화 기술 연구 동향

  • Hong, YoungGee;Hur, JunBeom
    • Review of KIISC
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    • v.28 no.3
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    • pp.11-17
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    • 2018
  • 세계적 열풍의 중심인 비트코인에는 많은 이슈가 발생하고 있다. 특히 비트코인의 익명성은 사회적으로 중요한 문제이다. 비트코인이 익명성을 보장하지 못할 경우 거래내역이 공개되어 프라이버시가 노출될 수 있다. 반대로 비트코인이 익명성을 보장할 경우 마약 거래, 자금 세탁, 랜섬웨어 공격 등의 각종 범죄가 발생할 수 있다. 이밖에도 다양한 상황에 적절한 대처를 하기 위해서는 비트코인 기술에 대한 정리와 이해가 필요하다. 본 논문에서는 비트코인의 익명성을 약화시키는 클러스터링 기술과, 비트코인의 익명성을 강화시키는 믹싱 프로토콜 기술에 대한 연구 흐름을 정리하였다.

Automatic Building Ontology Techniques for RESTful Web Services (RESTful 웹 서비스를 위한 온톨로지 자동 구축 기법)

  • Lee, Yong-Ju
    • Proceedings of the Korea Information Processing Society Conference
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    • 2011.04a
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    • pp.1415-1418
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    • 2011
  • 최근 웹상에 이용 가능한 RESTful 웹 서비스들의 수가 급격하게 증가됨에 따라 사용자들이 적합한 웹 서비스를 찾는 것은 매우 중요한 이슈로 대두되었다. 그러나 기존의 키워드 기반 검색 방법은 나쁜 재현율과 나쁜 정확률 때문에 문제가 많다. 본 논문에서는 매개변수 클러스터링 기법에 패턴 분석 기법을 추가한 하나의 새로운 시맨틱 온톨로지 구축 방법을 제안한다. 이를 통해 온톨로지를 자동 구축하여 시맨틱 정보의 주석처리 부담을 줄일 수 있고, 보다 효율적인 웹 서비스 검색을 지원한다.

Intrusion Detection based on Clustering a Data Stream (데이터 스트림 클러스터링을 이용한 침임탐지)

  • Oh Sang-Hyun;Kang Jin-Suk;Byun Yung-Cheol
    • Proceedings of the Korea Contents Association Conference
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    • 2005.11a
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    • pp.529-532
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    • 2005
  • In anomaly intrusion detection, how to model the normal behavior of activities performed by a user is an important issue. To extract the normal behavior as a profile, conventional data mining techniques are widely applied to a finite audit data set. However, these approaches can only model the static behavior of a user in the audit data set This drawback can be overcome by viewing the continuous activities of a user as an audit data stream. This paper proposes a new clustering algorithm which continuously models a data stream. A set of features is used to represent the characteristics of an activity. For each feature, the clusters of feature values corresponding to activities observed so far in an audit data stream are identified by the proposed clustering algorithm for data streams. As a result, without maintaining any historical activity of a user physically, new activities of the user can be continuously reflected to the on-going result of clustering.

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Energy-Efficient Clustering Scheme using Candidates Nodes of Cluster Head (클러스터헤더 후보노드를 이용한 에너지 효율적인 클러스터링 방법)

  • Cho, Young-Bok;Kim, Kwang-Deuk;You, Mi-Kyeong;Lee, Sang-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.3
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    • pp.121-129
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    • 2011
  • One of the major challenges of minimum energy consumption for wireless sensor networks(WSN) environment. LEACH protocol is hierarchical routing protocol that obtains energy efficiency by using clustering. However, LEACH protocol in each round, because the new cluster configuration, cluster configuration, whenever the energy consumed shorten the life of the network. Therefore in this paper, the cluster is formed in WSN environment in early stage and the problems with energy waste have been solved by selecting C-node. In the initial round of proposed model uses 26 percent more than traditional LEACH energy consumption. However, as the round is ongoing, it has been proved by the network simulation tool that the waste of energy could be diminished up to 35%.

Clustering and Pattern Analysis for Building Semantic Ontologies in RESTful Web Services (RESTful 웹 서비스에서 시맨틱 온톨로지를 구축하기 위한 클러스터링 및 패턴 분석 기법)

  • Lee, Yong-Ju
    • Journal of Internet Computing and Services
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    • v.12 no.4
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    • pp.119-133
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    • 2011
  • With the advent of Web 2.0, the use of RESTful web services is expected to overtake that of the traditional SOAP-based web services. Recently, the growing number of RESTful web services available on the web raises the challenging issue of how to locate the desired web services. However, the existing keyword searching method is insufficient for the bad recall and the bad precision. In this paper, we propose a novel building semantic ontology method which employs both the clustering technique based on association rules and the semantic analysis technique based on patterns. From this method, we can generate ontologies automatically, reduce the burden of semantic annotations, and support more efficient web services search. We ran our experiments on the subset of 168 RESTful web services downloaded from the PregrammableWeb site. The experimental results show that our method achieves up to 35% improvement for recall performance, and up to 18% for precision performance compared to the existing keyword searching method.

CUCE: clustering protocol using node connectivity and node energy (노드 연결도와 에너지 정보를 이용한 개선된 센서네트워크 클러스터링 프로토콜)

  • Choi, Hae-Won
    • Journal of Korea Society of Industrial Information Systems
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    • v.17 no.4
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    • pp.41-50
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    • 2012
  • Network life time is very important issue for wireless sensor network(WSN). It is very important to design sensor networks for sensors to utilize their energies in effective ways. A-PEGASIS that basically bases on PEGASIS and enhances in two aspects-an elegant chain generation algorithm and periodical update of chains. However, it has problems in the chain generation mechanism and some possibility of network partitioning or sensing hole problem in the network, in LEACH related protocols. This dissertation proposes a new clustering protocol to solve the co-shared problems in the previous protocols. The basic idea of our scheme is using the table for node connectivity. The results show that the network life time would be extended in about 1.8 times longer than LEACH and 1.5 times longer than PEGASIS-A.

Clustering and Routing Algorithm for QoS Guarantee in Wireless Sensor Networks (무선 센서 네트워크에서 QoS 보장을 위한 클러스터링 및 라우팅 알고리즘)

  • Kim, Soo-Bum;Kim, Sung-Chun
    • The KIPS Transactions:PartC
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    • v.17C no.2
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    • pp.189-196
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    • 2010
  • The LEACH does not use flooding method for data transmission and this makes low power consumption. So performance of the WSN is increased. On the other hand, QoS based algorithm which use restricted flooding method in WSN also achieves low power consuming rate by reducing the number of nodes that are participated in routing path selection. But when the data is delivered to the sink node, the LEACH choose a routing path which has a small hop count. And it leads that the performance of the entire network is worse. In the paper we propose a QoS based energy efficient clustering and routing algorithm in WSN. I classify the type of packet with two classes, based on the energy efficiency that is the most important issue in WSN. We provide the differentiated services according to the different type of packet. Simulation results evaluated by the NS-2 show that proposed algorithm extended the network lifetime 2.47 times at average. And each of the case in the class 1 and class 2 data packet, the throughput is improved 312% and 61% each.

A Multi-Dimensional Issue Clustering from the Perspective Consumers' Interests and R&D (소비자 선호 이슈 및 R&D 관점에서의 다차원 이슈 클러스터링)

  • Hyun, Yoonjin;Kim, Namgyu;Cho, Yoonho
    • Journal of Information Technology Services
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    • v.14 no.1
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    • pp.237-249
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    • 2015
  • The volume of unstructured text data generated by various social media has been increasing rapidly; therefore, use of text mining to support decision making has also been increasing. Especially, issue Clustering-determining a new relation with various issues through clustering-has gained attention from many researchers. However, traditional issue clustering methods can only be performed based on the co-occurrence frequency of issue keywords in many documents. Therefore, an association between issues that have a low co-occurrence frequency cannot be discovered using traditional issue clustering methods, even if those issues are strongly related in other perspectives. Therefore, issue clustering that fits each of criteria needs to be performed by the perspective of analysis and the purpose of use. In this study, a multi-dimensional issue clustering is proposed to overcome the limitation of traditional issue clustering. We assert, specifically in this study, that issue clustering should be performed for a particular purpose. We analyze the results of applying our methodology to two specific perspectives on issue clustering, (i) consumers' interests, and (ii) related R&D terms.

'Korean Wave' News Analysis Using News Big Data ('한류' 경향에 관한 국내 언론 기사 빅데이터 분석 연구)

  • Hwang, Seo-I;Park, Jeong-Bae
    • Journal of Korea Entertainment Industry Association
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    • v.14 no.5
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    • pp.1-14
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    • 2020
  • This study conducted a topic modeling and semantic network analysis of 'korean wave' and its meaning in Korean society from 2000 to 2019 by applying an agenda setting theory. For this purpose, a total of 197,992 newspaper articles which reported 'korean wave' issues were analyzed by applying topic modeling and semantic network analysis. As a result, first, the word 'korean wave' mainly appeared in korean-related regions in the korean press. culture and economy. second, a total of 9 topics related to korean wave issues appeared. This was followed by 'broadcast', 'export', 'domestic and foreign affairs', 'education', 'beauty and fashion', 'music and performance', 'tourism', 'media(platform)', and 'region'. Lastly, korean wave was mainly discussed at the cultural and economic ares. In addition, it was clustered into five characteristics: 'cultural hallyu', 'business hallyu', 'education', 'environment', and 'geography'.