• Journal of Information Technology Applications and Management
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• 제18권1호
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• pp.15-39
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• 2011

A deeper understanding of how organizations behave as social complex adaptive systems is needed. In this paper we demonstrate how the Leadership Invigorating Flows of Energies model can help with this understanding. The model highlights the role of emergent leadership as a force encouraging the creation, diffusion, and utilization of knowledge through self-organizing mechanisms. We illustrate our approach by examining Wikipedia and show how it can be described as a social CAS. Our analysis of Wikipedia describes how emerging intrapreneurship behaviors result in dynamic flows of knowledge and self-organizing feedback mechanisms across the organization. We provide implications for organization studies and present evidence to support claims made by advocates of complexity theory. We conclude by proposing that Wikipedia can be seen as a new form of organization, and finish with a brief note highlighting a possible way forward.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2022년도 추계학술발표대회
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• pp.374-376
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• 2022

Community detection is meaningful research in social network analysis, and many existing studies use graph theory analysis methods to detect communities. This paper proposes a method to detect community by detecting maximal cliques and obtain the high influence cliques by high influence nodes, then merge the cliques with high similarity in social network.

• Journal of Information Science Theory and Practice
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• 제12권1호
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• pp.39-59
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• 2024

An online social network is a platform that is continuously expanding, which enables groups of people to share their views and communicate with one another using the Internet. The social relations among members of the public are significantly improved because of this gesture. Despite these advantages and opportunities, criminals are continuing to broaden their attempts to exploit people by making use of techniques and approaches designed to undermine and exploit their victims for criminal activities. The field of digital forensics, on the other hand, has made significant progress in reducing the impact of this risk. Even though most of these digital forensic investigation techniques are carried out manually, most of these methods are not usually appropriate for use with online social networks due to their complexity, growth in data volumes, and technical issues that are present in these environments. In both civil and criminal cases, including sexual harassment, intellectual property theft, cyberstalking, online terrorism, and cyberbullying, forensic investigations on social media platforms have become more crucial. This study explores the use of machine learning techniques for addressing criminal incidents on social media platforms, particularly during forensic investigations. In addition, it outlines some of the difficulties encountered by forensic investigators while investigating crimes on social networking sites.

• 경영과정보연구
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• 제3권
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• pp.15-45
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• 1999

Processing techniques of remote sensed image data using computer have been recognized very necessary techniques to all social fields, such as, environmental observation, land cultivation, resource investigation, military trend grasp and agricultural product estimation, etc. Especially, accurate classification and analysis to remote sensed image da are important elements that can determine reliability of remote sensed image data processing systems, and many researches have been processed to improve these accuracy of classification and analysis. Traditionally, remote sensed image data processing systems have been processed 2 or 3 selected bands in multiple bands, in this time, their selection criterions are statistical separability or wavelength properties. But, it have be bring up the necessity of bands selection method by data distribution characteristics than traditional bands selection by wavelength properties or statistical separability. Because data sensing environments change from multispectral environments to hyperspectral environments. In this paper for efficient data classification in multispectral bands environment, a band feature extraction method using the Rough sets theory is proposed. First, we make a look up table from training data, and analyze the properties of experimental multispectral image data, then select the efficient band using indiscernibility relation of Rough set theory from analysis results. Proposed method is applied to LANDSAT TM data on 2 June 1992. From this, we show clustering trends that similar to traditional band selection results by wavelength properties, from this, we verify that can use the proposed method that centered on data properties to select the efficient bands, though data sensing environment change to hyperspectral band environments.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 추계학술발표대회
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• pp.528-531
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• 2021

Nowadays recommendation systems are so ubiquitous, where our many decisions are being done by the means of them. We can see recommendation systems in all areas of our daily life. Therefore the research of this sphere is still so active. So far many research papers were published for clothing recommendations as well. In this paper, we propose the clothing-recommendation system according to user emotion and weather information. We used social media to analyze users' 6 basic emotions according to Paul Eckman theory and match the colour of clothing. Moreover, getting weather information using visualcrossing.com API to predict the kind of clothing. For sentiment analysis, we used Emotion Lexicon that was created by using Mechanical Turk. And matching the emotion and colour was done by applying Hayashi's Quantification Method III.

• 한국조경학회지
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• 제28권2호
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• pp.49-60
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• 2000

The purpose of this study is to overview domestic and foreign trends in the study of the landscape evaluation through new framework of landscape evaluation studies. 108 studies on the landscape evaluation are summarized and categorized into theoretical studies, verification of theories, development of evaluation methods and applications in physical planning. Major theories in the landscape evaluation came from the psycho-physics, the evolutionary theory ann the cultural-learning theory, and were verified and applied into physical planning. Early experimental researches on landscape evaluation, based on psycho-physics, were focused on relatively simple responses to landscapes. But many studies have been gradually related to the evolutionary theory and the cultural learning theory, emphasizing biological and cultural effects on landscape evaluation. Especially, Appleton's Prospect-Refuge theory' and Kaplans' 'Information Processing model' have very strong influence in landscape evaluation. Relatively there have been many application researches in Korea, which tells there have been strong needs to solve pending practical problems caused by the rapid economic and social growth for several decades. Almost of applications in physical planning are focused on physical features of landscapes, but for more comprehensive landscape evaluation, many other factors such as cognitive and sociocultural variables should be integrated into the whole evaluation system. As a result of reviewing of landscape evaluation studies, I found the overall domestic and foreign trends and the necessity of more research on the applications in physical planning. Because this study mainly focused on academic researches, for more appropriate landscape evaluation and management there should be more practical researches including various approaches.

• Journal of Information Processing Systems
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• 제14권2호
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• pp.455-468
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• 2018

The concepts of graph theory are applied to model and analyze dynamics of computer networks, biochemical networks and, semantics of social networks. The analysis of dynamics of complex networks is important in order to determine the stability and performance of networked systems. The analysis of non-stationary and nonlinear complex networks requires the applications of ordinary differential equations (ODE). However, the process of resolving input excitation to the dynamic non-stationary networks is difficult without involving external functions. This paper proposes an analytical formulation for generating solutions of nonlinear network ODE systems with functional decomposition. Furthermore, the input excitations are analytically resolved in linearized dynamic networks. The stability condition of dynamic networks is determined. The proposed analytical framework is generalized in nature and does not require any domain or range constraints.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2014년도 추계학술발표대회
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• pp.1136-1138
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• 2014

Recently, predicting personality with the help of smartphone usage is become very interesting and attention grabbing topic in the field of research. At present there are some approaches towards detecting a user's personality which uses the smartphones usage data, such as call detail records (CDRs), the usage of short message services (SMSs) and the usage of social networking services application. In this paper, we focus on the predicting user attitude based on MBTI theory by using their smartphone usage data. We used Naïve Bayes and SVM classifier for classifying user personalities by extracting some features from smartphone usage data. From analysis it is observed that, SVM classifier works well as compared to Naïve Bayes.

• Journal of Information Science Theory and Practice
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• 제11권2호
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• pp.67-81
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• 2023

This paper presents a dynamic development of an ontology-based statistical information system supporting the collection, storage, processing, analysis, and the presentation of statistical knowledge at the national scale. To accomplish this, we propose a data mining technique to dynamically collect data relating to citizens from publicly available data sources; the collected data will then be structured, classified, categorized, and integrated into an ontology. Moreover, an intelligent platform is proposed in order to generate quantitative and qualitative statistical information based on the knowledge stored in the ontology. The main aims of our proposed system are to digitize administrative tasks and to provide reliable statistical information to governmental, economic, and social actors. The authorities will use the ontology-based statistical information system for strategic decision-making as it easily collects, produces, analyzes, and provides both quantitative and qualitative knowledge that will help to improve the administration and management of national political, social, and economic life.

• Journal of Preventive Medicine and Public Health
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• 제26권4호
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• pp.508-533
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• 1993

지금까지 우리나라의 국민들의 예방행태와 질병행태, 그리고 환자역할에 대하여 기존에 발표된 자료를 중심으로 재해석을 기하여 보았다. 물론 이 발표에서 사용된 자료들이 정확하며 타당한 자료인가에 대해서는 반드시 그렇다라고 답변할 수는 없다. 다만 우리나라에서의 건강관련행태를 설명하기 위해서는 자료의 한계라는 현실을 감안하지 않을 수 없다는 사실을 이해해주기 바란다. 우리나라국민들의 건강행태는 과거에 비해 상당히 변화하고 있으나 계층간의 행태의 차이, 변화의 원인 등에 대해서는 아직 연구가 미흡하다. 지금까지 이루어진 행태연구들이 정합적인 모형을 사용하고 있다고 보기 어려운 것이 그 원인의 하나 일 것이다. 새로이 개발된 모형들을 적용하기 위한 노력이 필요하며, 사용되는 변수의 타당성에 대한 연구도 필요하다. 행태와 관련된 연구에서 사용되는 변수들이 사회문화의 산물이라는 사실을 생각하면 우리나름대로의 변수정의가 있어야 한다는 것은 지극히 당연하다 하겠다. 끝으로 행태를 연구함에 있어 인간의 의식은 사회구조의 산물이라는 사실을 명심할 필요가 있다. 루카치는 자본주의 사회에서는 노동자의 계급의식 역시 자본주의 구조의 산물일 수 있다 하였다. 이런 의미에서 지식, 태도, 행태 등에 대한 연구는 사회구조의 총체성에 대한 인식을 요구한다. 만일 그렇지 않은 경우에는 행태연구를 통한 결과가 희생자비난의 논리로 악순환할 가능성이 높기 때문이다.