• Journal of KIISE
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• v.41 no.12
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• pp.1117-1125
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• 2014

Folksonomy data, which is derived from social tagging systems, is a useful source for understanding a user's intention and interest. Using the folksonomy data, it is possible to create an accurate user profile which can be utilized to build a personalized search system. However there are limitations in some of the traditional methods such as Vector Space Model(VSM) for user profiling and similarity computation. This paper suggests a novel method with graph-based user and document profile which uses the proximity information of query terms to improve personalized search. We demonstrate the performance of the suggested method by comparing its performance with several state-of-the-art VSM based personalization models in two different folksonomy datasets. The results show that the proposed model constantly outperforms the other state-of-the-art personalization models. Furthermore, the parameter sensitivity results show that the proposed model is parameter-free in that it is not affected by the idiosyncratic nature of datasets.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2016.11a
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• pp.334-338
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• 2016

본 연구에서는 한국공항의 테러방비와 특수경비원들의 효율적 보안검색을 위하여 비정상 행동탐지기법과 관련한 각 국의 프로그램 및 자료를 조사 분석하였다. 그리고 우리나라의 상황에 적합한 한국형 행동탐지기법 프로그램을 개발을 제시하였다. 우선 한국공항 특수경비원들의 비정상 행동탐지기법 도입을 위하여 각국의 프로파일링의 유형과 행동탐지기법을 조사 분석하고 한국형 행동탐지기법 프로그램을 자체 개발하는 연구를 수행하였다. 이를 통하여 국내 항공 테러방비를 위한 비정상행정탐지기법 도입의 필요성과 특수경비원의 보안검색 효율화와 항공보안의 학문적 도약을 위한 기초적 자료를 제시하고자 한다.

• The Journal of the Korea Contents Association
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• v.12 no.6
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• pp.413-423
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• 2012

Offender profiling, as a crime investigation technique, aims to respond more effectively to violent crimes. However, attitude that police investigators hold toward offender profiling is quite skeptical, which prevents offender profiling from making effective and practical contributions to police investigations. Therefore, the present study explored development strategies of offender profiling by examining perceptions of offender profiling among 156 Korean National Police University students. Furthermore, a total of 166 students from other universities also participated as a control group. As a result, participants showed positive attitude toward offender profiling, in terms of its necessity, effectiveness, and reliability. However, they believed that Korean police agencies are not making the good use of offender profiling and that profilers are not necessarily taking the lead in solving cases. In terms of the profiler education, the majority of the students who showed interest in becoming a profiler did not know what to learn and how to prepare for becoming one. Finally, limitations of the present study were discussed and suggestions for further research were made.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.135-140
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• 2021

In this paper, we propose an on-line mechanism that simultaneously detects cracks and profiling pavement blocks to detect the displacement of ground surface adjacent to the excavation in the urban area. The proposed method utilizes a 2D laser to profile the information about pavement blocks including the depth and distance among them. In particular, it is designed to enable the detection of cracks and portholes at runtime. For the experiment, real data was collected through Gocator, and trainng was carried out using Faster R-CNN. The performance evaluation shows that our detection precision and recall are more than 90% and the pavement blocks are profiled at the same time. Our proposed mechanism can be used for monitoring management to quantitatively detect the level of excavation risk before a large-scale ground collapse occurs.

• Journal of the Korea Society of Computer and Information
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• v.8 no.1
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• pp.103-113
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• 2003

Program Behavior Intrusion Detection Technique analyses system calls that called by daemon program or root authority, constructs profiles. and detectes anomaly intrusions effectively. Anomaly detections using system calls are detected only anomaly processes. But this has a Problem that doesn't detect affected various Part by anomaly processes. To improve this problem, the relation among system calls of processes is represented by bayesian probability values. Application behavior profiling by Bayesian Network supports anomaly intrusion informations . This paper overcomes the Problems of various intrusion detection models we Propose effective intrusion detection technique using Bayesian Networks. we have profiled concisely normal behaviors using behavior context. And this method be able to detect new intrusions or modificated intrusions we had simulation by proposed normal behavior profiling technique using UNM data.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.2
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• pp.285-308
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• 2010

This study analyzes the intellectual structure in domestic research of the Housing field, by utilizing text mining technique. Unlike the existing research that mainly uses text clustering in statistical analyses to identify subject specialties, core authors, and relationships between research areas, this study applied author profiling and factor analysis. To supplement the analysis of intellectual structure generated by text mining, and to perform evaluation on intellectual structure itself, two professionals in the housing field were interviewed. The intellectual structure, generated through text mining, was evaluated and showed its division of valid research areas that is slightly different from the traditional intellectual structure in the housing field.

• The KIPS Transactions:PartC
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• v.10C no.2
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• pp.119-124
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• 2003

Although there have been many studies on using finite automata for intrusion detection, it has been a difficult problem to generate compact finite automata automatically. In a previous research an approach to profile normal behaviors using finite automata was proposed. They divided the system call sequence of each process into three parts prefix, main portion, and suffix, and then substituted macros for frequently occurring substrings. However, the procedure was not automatic. In this paper we present algorithms to automatically generate intrusion detection automata from the sequence of system calls resulting from the normal runs of the programs. We also show the effectiveness of the proposed method through experiments.

• Journal of the Korean Society for information Management
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• v.31 no.3
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• pp.293-311
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• 2014

This study explored the research trends on Twitter in Korea by informetric methods. All 539 articles on Twitter published from 2009 to the April of 2014 were obtained from the KCI. Only article titles, abstracts, and keywords by authors were used in analysis. Academic journals in many different disciplines where Twitter articles were produced were analysed by profiling, and then, the subject areas of researches on Twitter were analysed by co-word analysis. The results of this study showed that Twitter-related papers were published in as many as 53 disciplines with journalism, business administration, and computer science to be core fields. It was also found that the core subject areas are political issues and business.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.22 no.4
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• pp.21-44
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• 2011

This study aims to analyze research domains and trends of reading education in Korea and, suggest future research direction of this field. First, In order to identify the overview of research in terms of productivity, A basic analysis was performed based on 1,465 articles of domestic serials(1935~2011). Second, The analysis of intellectual structure using author profiling as a technique of text mining was performed based on 652 papers of domestic journals(2000~2011). Third, Depending on the results of these analysis, this study suggested the directions of future research of the field.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.187-194
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• 2021

OSINT(Open Source Intelligence), rapidly increasing on the surface web in various forms, can also be used for criminal investigations by using profiling. This technique has become quite common in foreign investigative agencies such as the United States. On the other hand, in Korea, it is not used a lot, and there is a large deviation in the quantity and quality of information acquired according to the experience and knowledge level of investigator. Unlike Bazzell's most well-known model, we designed a Korean-style OSINT-based profiling technique that considers the Korean web environment and provides timeline information, focusing on the improved workflow. The database schema to improve the efficiency of profiling is also presented. Using this, we can obtain search results that guarantee a certain level of quantity and quality. And it can also be used as a standard training course. To increase the effectiveness and efficiency of criminal investigations using this technique, it is necessary to strengthen the legal basis and to introduce automation technologies.