• Title/Summary/Keyword: Graph Mining

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Adaptive Customer Relation Management Strategies using Association Rules (연관 규칙을 이용한 적응적 고객 관계 관리 전략)

  • Han, Ki-Tae;Chung, Kyung-Yong;Baek, Jun-Ho;Kim, Jong-Hun;Ryu, Joong-Kyung;Lee, Jung-Hyun
    • Proceedings of the Korea Contents Association Conference
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    • 2008.05a
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    • pp.84-86
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    • 2008
  • The customer relation marketing in which companies can utilize to control and to get the filtered information efficiently has appeared. It is applying data mining to build the management that can even predict and recommend products to customers. In this paper, we proposed the adaptive customer relation management strategies using the association rules of data mining. The proposed method uses the association rules composes frequent customers with occurrence of candidate customer set creates the rules of associative customers. We analyzed the efficient feature of purchase customers using the hyper graph partition according to the lift of creative association rules. Therefore, we discovered strategies of the cross-selling and the up-selling about customers.

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Visualization of movie recommendation system using the sentimental vocabulary distribution map

  • Ha, Hyoji;Han, Hyunwoo;Mun, Seongmin;Bae, Sungyun;Lee, Jihye;Lee, Kyungwon
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.5
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    • pp.19-29
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    • 2016
  • This paper suggests a method to refine a massive collective intelligence data, and visualize with multilevel sentiment network, in order to understand information in an intuitive and semantic way. For this study, we first calculated a frequency of sentiment words from each movie review. Second, we designed a Heatmap visualization to effectively discover the main emotions on each online movie review. Third, we formed a Sentiment-Movie Network combining the MDS Map and Social Network in order to fix the movie network topology, while creating a network graph to enable the clustering of similar nodes. Finally, we evaluated our progress to verify if it is actually helpful to improve user cognition for multilevel analysis experience compared to the existing network system, thus concluded that our method provides improved user experience in terms of cognition, being appropriate as an alternative method for semantic understanding.

Fabrication of Three-Dimensional Scanning System for Inspection of Massive Sinkhole Disaster Sites (대형 싱크홀 재난 현장 조사용 3차원 형상화 장비 구현)

  • Kim, Soolo;Yoon, Ho-Geun;Kim, Sang-Wook
    • The Journal of Korea Robotics Society
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    • v.15 no.4
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    • pp.341-349
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    • 2020
  • Recently, interest in ground subsidence in urban areas has increased after a large sinkhole occurred near the high-story building area in Jamsil, Seoul, Korea, in 2014. If a massive sinkhole occurs in an urban area, it is crucial to assess its risk rapidly. Access to humans for on-site safety diagnosis may be difficult because of the additional risk of collapse in the disaster area. Generally, inspection using drones equipped with high-speed lidar sensors can be utilized. However, if the sinkhole is created vertically to a depth of 100 m, similar to the sinkhole in Guatemala, the drone cannot be applied because of the wireless communication limit and turbulence inside the sinkhole. In this study, a three-dimensional (3D) scanning system was fabricated and operated using a towed cable in a massive vertical sinkhole to a depth of 200 m. A high-speed lidar sensor was used to obtain a continuous cross-sectional shape at a certain depth. An inertial-measuring unit was applied to compensate for the error owing to the rotation and pendulum movement of the measuring unit. A reconstruction algorithm, including the compensation scheme, was developed. In a vertical hole with a depth of 180 m in the mining area, the fabricated system was applied to scan 0-165 m depth. The reconstructed shape was depicted in a 3D graph.

Directed Graph by Integrating Web Document Hyperlink and Web Access Log for Web Mining (웹 마이닝을 위한 웹 문서 하이퍼링크와 웹 접근로그를 통합한 방향그래프)

  • Park, Chul-Hyun;Lee, Seong-Dae;Kwak, Yong-Won;Jeon, Sung-Hwan;Park, Hyu-Chan
    • Proceedings of the Korean Information Science Society Conference
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    • 2005.11b
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    • pp.16-18
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    • 2005
  • 웹은 사용자가 원하는 정보를 쉽고 정확하게 검색할 수 있도록 웹 문서를 자료구조화하여 보다 신뢰성 있는 패턴을 추출하고 사용자의 특성과 행동 패턴을 적용하여 개인화 하여야한다. 본 논문에서는 개인화하기 위한 전처리 과정으로서 웹 문서를 구조화 하는 방법을 제안한다. 제안 방법은 기본적으로 웹 문서 태그의 하이퍼링크를 깊이 우선 탐색 알고리즘을 사용하여 방향그래프를 만드는 것이다. 이때 웹 문서 태그 탐색 시 플래시, 스크립트 등의 찾기 힘든 하이퍼링크를 찾는 문제와 '뒤로' 버튼 사용 시 웹 접근로그에 기록되지 않는 문제점을 보완한다. 이를 위해 클릭 스트림을 스택에 저장하여 이미 만들어진 방향그래프와 비교하여 새롭게 찾은 정점과 간선을 추가함으로써 보다 신뢰성높은 방향그래프를 만든다.

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An Empirical Study of Absolute-Fairness Maximal Balanced Cliques Detection Based on Signed Attribute Social Networks: Considering Fairness and Balance

  • Yixuan Yang;Sony Peng;Doo-Soon Park;Hye-Jung Lee;Phonexay Vilakone
    • Journal of Information Processing Systems
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    • v.20 no.2
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    • pp.200-214
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    • 2024
  • Amid the flood of data, social network analysis is beneficial in searching for its hidden context and verifying several pieces of information. This can be used for detecting the spread model of infectious diseases, methods of preventing infectious diseases, mining of small groups and so forth. In addition, community detection is the most studied topic in social network analysis using graph analysis methods. The objective of this study is to examine signed attributed social networks and identify the maximal balanced cliques that are both absolute and fair. In the same vein, the purpose is to ensure fairness in complex networks, overcome the "information cocoon" bottleneck, and reduce the occurrence of "group polarization" in social networks. Meanwhile, an empirical study is presented in the experimental section, which uses the personal information of 77 employees of a research company and the trust relationships at the professional level between employees to mine some small groups with the possibility of "group polarization." Finally, the study provides suggestions for managers of the company to align and group new work teams in an organization.

Text Mining Analysis Technique on ECDIS Accident Report (텍스트 마이닝 기법을 활용한 ECDIS 사고보고서 분석)

  • Lee, Jeong-Seok;Lee, Bo-Kyeong;Cho, Ik-Soon
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.25 no.4
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    • pp.405-412
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    • 2019
  • SOLAS requires that ECDIS be installed on ships of more than 500 gross tonnage engaged in international navigation until the first inspection arriving after July 1, 2018. Several accidents related to the use of ECDIS have occurred with its installation as a new major navigation instrument. The 12 incident reports issued by MAIB, BSU, BEAmer, DMAIB, and DSB were analyzed, and the cause of accident was determined to be related to the operation of the navigator and the ECDIS system. The text was analyzed using the R-program to quantitatively analyze words related to the cause of the accident. We used text mining techniques such as Wordcloud, Wordnetwork and Wordweight to represent the importance of words according to their frequency of derivation. Wordcloud uses the N-gram model as a way of expressing the frequency of used words in cloud form. As a result of the uni-gram analysis of the N-gram model, ECDIS words were obtained the most, and the bi-gram analysis results showed that the word "Safety Contour" was used most frequently. Based on the bi-gram analysis, the causative words are classified into the officer and the ECDIS system, and the related words are represented by Wordnetwork. Finally, the related words with the of icer and the ECDIS system were composed of word corpus, and Wordweight was applied to analyze the change in corpus frequency by year. As a result of analyzing the tendency of corpus variation with the trend line graph, more recently, the corpus of the officer has decreased, and conversely, the corpus of the ECDIS system is gradually increasing.

SNS Message as an Political PR Campaign Strategy: Focusing on the 21st General Election (정치 PR 전략으로서의 SNS 메시지 : 21대 총선을 중심으로)

  • Cha, Young-Ran
    • The Journal of the Korea Contents Association
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    • v.20 no.9
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    • pp.208-223
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    • 2020
  • In the 21st general election held in April 15, 2020, the importance of social media as an election campaigning tool became more prominent when engaged with Corona 19. Therefore, in this study, various studies were conducted to establish SNS strategy as an election campaign tool. This study analyzed the contents of SNS (Facebook, Twitter, YouTube) activities as an election campaign tool to analyze messages on social media messages of candidates Lee Nak-yeon and candidate Hwang Kyo-an of Jongno-gu, Seoul during the 2020 21st National Assembly election. Data collection mainly analyzed posts from each candidate's official account, and the research method used text analysis using the R program. Word cloud, comparative analysis, q-graph analysis, LDA, and STM analysis were used during text analysis. In addition, the analysis result was confirmed to be statistically significant through correlation analysis. As a result of research, candidate Lee Nak-yeon's election includes corona, people, problems, crisis, suffering, and wisdom, which indicates that the crisis caused by corona must be overcome through any means possible. On the other hand, candidate Hwang Kyo-an's election includes Moon Jae-in, the regime, save, the fatherland, the judge, and the economy. And from the perspective of political publicity, candidate Lee Nak-yeon made a lot of acclaims, while candidate Hwang Kyo-an made a lot of attacks, and both themes emphasized the policy rather than the image.

Network Structures of The Metropolitan Seoul Subway Systems (서울 대도시권 지하철망의 구조적 특성 분석)

  • Park, Jong-Soo;Lee, Keum-Sook
    • Journal of the Economic Geographical Society of Korea
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    • v.11 no.3
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    • pp.459-475
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    • 2008
  • This study analyzes the network structure of the Metropolitan Seoul subway system by applying complex network analysis methods. For the purpose, we construct the Metropolitan Seoul subway system as a network graph, and then calculate various indices introduced in complex network analysis. Structural characteristics of Metropolitan Seoul subway network are discussed by these indices. In particular, this study determines the shortest paths between nodes based on the weighted distance (physical and time distance) as well as topological network distance, since urban travel movements are more sensitive for them. We introduce an accessibility measurement based on the shortest distance both in terms of physical distance and network distance, and then compare the spatial structure between two. Accessibility levels of the system have been getting up overall, and thus the accessibility gaps have been getting lessen between center located subway stops and remote ones during the last 10 years. Passenger traffic volumes are explored from real passenger transaction databases by utilizing data mining techniques, and mapped by GIS. Clear differences reveal between the spatial patterns of real passenger flows and accessibility. That is, passenger flows of the Metropolitan Seoul subway system are related with population distribution and land use around subway stops as well as the accessibility supported by the subway network.

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Automated Development of Rank-Based Concept Hierarchical Structures using Wikipedia Links (위키피디아 링크를 이용한 랭크 기반 개념 계층구조의 자동 구축)

  • Lee, Ga-hee;Kim, Han-joon
    • The Journal of Society for e-Business Studies
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    • v.20 no.4
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    • pp.61-76
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    • 2015
  • In general, we have utilized the hierarchical concept tree as a crucial data structure for indexing huge amount of textual data. This paper proposes a generality rank-based method that can automatically develop hierarchical concept structures with the Wikipedia data. The goal of the method is to regard each of Wikipedia articles as a concept and to generate hierarchical relationships among concepts. In order to estimate the generality of concepts, we have devised a special ranking function that mainly uses the number of hyperlinks among Wikipedia articles. The ranking function is effectively used for computing the probabilistic subsumption among concepts, which allows to generate relatively more stable hierarchical structures. Eventually, a set of concept pairs with hierarchical relationship is visualized as a DAG (directed acyclic graph). Through the empirical analysis using the concept hierarchy of Open Directory Project, we proved that the proposed method outperforms a representative baseline method and it can automatically extract concept hierarchies with high accuracy.

Analysis on Status and Trends of SIAM Journal Papers using Text Mining (텍스트마이닝 기법을 활용한 미국산업응용수학 학회지의 연구 현황 및 동향 분석)

  • Kim, Sung-Yeun
    • The Journal of the Korea Contents Association
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    • v.20 no.7
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    • pp.212-222
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    • 2020
  • The purpose of this study is to understand the current status and trends of the research studies published by the Society for Industrial and Applied Mathematics which is a leader in the field of industrial mathematics around the world. To perform this purpose, titles and abstracts were collected from 6,255 research articles between 2016 and 2019, and the R program was used to analyze the topic modeling model with LDA techniques and a regression model. As the results of analyses, first, a variety of studies have been studied in the fields of industrial mathematics, such as algebra, discrete mathematics, geometry, topological mathematics, probability and statistics. Second, it was found that the ascending research subjects were fluid mechanics, graph theory, and stochastic differential equations, and the descending research subjects were computational theory and classical geometry. The results of the study, based on the understanding of the overall flows and changes of the intellectual structure in the fields of industrial mathematics, are expected to provide researchers in the field with implications of the future direction of research and how to build an industrial mathematics curriculum that reflects the zeitgeist in the field of education.