• The Journal of Bigdata
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• v.5 no.1
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• pp.55-63
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• 2020

This study proposed an approach of clustering collective users' activities of location-based social networks using check-in data of Foursquare users in Seoul. In order to cluster the collective activities, we generated sequential rules of the activities using sequential rule mining, and then constructed activity networks based on the rules. We analyzed the activity networks to identify network structure and hub activities, and clustered the activities within the networks. Unlike previous studies that analyzed activity transition patterns of location-based social network users, this study focused on analyzing the structure and clusters of successive activities. Hubs and clusters of activities with the approach proposed in this study can be used for location-based services and marketing. They could also be used in the public sector, such as infection prevention and urban policies.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.249-255
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• 2014

Recently, creation and sharing of information make progress actively through the SNS(Social Network Service) such as twitter, facebook and so on. It is necessary to extract the knowledge from aggregated information and data mining is one of the knowledge based approach. Especially, emotion analysis is a recent subdiscipline of text classification, which is concerned with massive collective intelligence from an opinion, policy, propensity and sentiment. In this paper, We propose the emotion prediction method, which extracts the significant key words and related key words from SNS paragraph, then predicts the emotion using these extracted emotion features.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2005.11a
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• pp.275-278
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• 2005

본 연구는 디스플레이 제품의 개발 및 생산과정에서 OSD 메뉴문자의 오류 유무를 검사하는 과정을 컴퓨터 비전기술을 사용하여 자동화하는 방법을 제안한다. 디스플레이 제품의 OSD 메뉴는 순차적인 제어과정을 통해서 제한된 디스플레이 영역에 여러 종류의 언어와 기호를 포함하는 형태로 출력된다. 기존의 제품개발 과정에서 이러한 메뉴 항목의 정확성을 검증하는 작업은 작업자의 육안에 의한 판단과 수작업에 의해 이루어지고 있는데, 이는 반복작업에 의한 집중력 저하 및 판단착오에 의한 오류의 가능성을 내재한다. 또한 작업자가 다양한 나라의 언어에 대한 문자형태와 기호표현의 특성을 이해하여야 하고, 검증작업 자체에 따르는 부수적인 시간과 노력을 필요로 한다. 이에 본 연구에서는 디스플레이 제품의 OSD 메뉴와 같이 특수한 구조를 갖는 문서영상에 대한 논리적인 구조분석을 통해서 연속적인 문서영상을 발생시키는 작업스케쥴러를 생성하고, 작업스케쥴러에 의해 순차적으로 발생된 영상문서에 대한 전처리, OSD 메뉴의 기하학적 구조분석 및 문자영역을 추출하는 방법과, 표준패턴 구축 및 원형정합에 의한 문자의 오류를 검증하는 방법과 오류를 관리하는 기법을 제안한다.

• Journal of the Economic Geographical Society of Korea
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• v.10 no.1
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• pp.44-63
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• 2007

The purpose of this study is to propose mining processes in the large trip-transaction database of the Metropolitan Seoul area and to analyze the spatial characteristics of travel behavior. For the purpose. this study introduces a mining algorithm developed for exploring trip patterns from the large trip-transaction database produced every day by transit users in the Metropolitan Seoul area. The algorithm computes trip chains of transit users by using the bus routes and a graph of the subway stops in the Seoul subway network. We explore the transfer frequency of the transit users in their trip chains in a day transaction database of three different years. We find the number of transit users who transfer to other bus or subway is increasing yearly. From the trip chains of the large trip-transaction database, trip patterns are mined to analyze how transit users travel in the public transportation system. The mining algorithm is a kind of level-wise approaches to find frequent trip patterns. The resulting frequent patterns are illustrated to show top-ranked subway stations and bus stops in their supports. From the outputs, we explore the travel patterns of three different time zones in a day. We obtain sufficient differences in the spatial structures in the travel patterns of origin and destination depending on time zones. In order to examine the changes in the travel patterns along time, we apply the algorithm to one day data per year since 2004. The results are visualized by utilizing GIS, and then the spatial characteristics of travel patterns are analyzed. The spatial distribution of trip origins and destinations shows the sharp distinction among time zones.

• Journal of KIISE:Software and Applications
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• v.31 no.5
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• pp.586-594
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• 2004

Because web documents become creation and disappearance rapidly, users require the recommend system that offers users to browse the web document conveniently and correctly. One largely untapped source of knowledge about large data collections is contained in the cumulative experiences of individuals finding useful information in the collection. Recommendation systems attempt to extract such useful information by capturing and mining one or more measures of the usefulness of the data. The existing Information Filtering system has the shortcoming that it must have user's profile. And Collaborative Filtering system has the shortcoming that users have to rate each web document first and in high-quantity, low-quality environments, users may cover only a tiny percentage of documents available. And dynamic recommendation system using the user browsing pattern also provides users with unrelated web documents. This paper classifies these web documents using the similarity between the web documents under the web document type and extracts the user browsing sequential pattern DB using the users' session information based on the web server log file. When user approaches the web document, the proposed Dynamic recommendation system recommends Top N-associated web documents set that has high similarity between current web document and other web documents and recommends set that has sequential specificity using the extracted informations and users' session information.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.490-492
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• 2000

본 논문에서는 방송영상 특성을 이용한 축구 경기 장면 분석을 제안한다. 동영상의 프레임들을 분할하기 위해서는 급격한 장면 변화나 화면의 색상과 같은 화면의 형식적인 변화가 주요 결정사항이다. 그러나 축구경기와 같은 동영상에서의 하이라이트는 화면의 형식적인 변화와는 조금 다른 의미를 가진다. 그러므로, 축구 경기 동영상에서 하이라이트 부분을 검출하기 위해서는 장면의 변화와 더불어 화면의 의미를 해석할 필요가 있다. 본 논문에서는 축구 경기 동영상의 모든 프레임을 순차적으로 검사한다. 임의의 프레임에 대하여 RGB 정보의 분석을 통하여 영상의 구성내용을 파악한 후, 구성 내용의 위치와 분포를 참조하여 하이라이트 여부를 판단한다. 제안된 방법에서는 RGB 값의 변화 문제를 해결하기 위하여, 주 RGB 범위 군집화(Dominant RGB Grouping) 방법을 통하여 임의의 영상에서 RGB 값의 변화에 최대한 덜 민감한 방법으로 대상의 RGB 정보를 취득할 수 있는 방법을 사용하였다.

• Journal of Digital Convergence
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• v.13 no.11
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• pp.383-390
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• 2015

In this study it placed the object of the present invention is to provide a more efficient user interface experience to analyze the structure information and the user experience when using the pattern of the search with the number of intended use of the smart phone. Naver and Daum were the results of the study will consist of 28 dogs and 15 each category Naver and Daum had both a top-down sequential structure. In the case of Naver it has raised the possibility of cognitive load through the use of duplicate content and excessive scrolling news Daum has been in the case of shopping categories at the bottom of this error was raised the possibility of using touch gestures.

• Journal of Information Technology Applications and Management
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• v.24 no.4
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• pp.187-196
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• 2017

It is urgent to prepare countermeasures for traffic congestion problems of Korea's metropolitan area where central functions such as economic, social, cultural, and education are excessively concentrated. Most users of public transportation in metropolitan areas including Seoul use the traffic cards. If various information is extracted from traffic big data produced by the traffic cards, they can provide basic data for transport policies, land usages, or facility plans. Therefore, in this study, we extract valuable information such as the subway passengers' frequent travel patterns from the big traffic data provided by the Seoul Metropolitan Government Big Data Campus. For this, we use a Hadoop (High-Availability Distributed Object-Oriented Platform) to preprocess the big data and store it into a Mongo database in order to analyze it by a sequential pattern data mining technique. Since we analysis the actual big data, that is, the traffic cards' data provided by the Seoul Metropolitan Government Big Data Campus, the analyzed results can be used as an important referenced data when the Seoul government makes a plan about the metropolitan traffic policies.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.267-273
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• 2016

Creation and Sharing of information which is structured data as well as various unstructured data. makes progress actively through the spread of mobile. Recently, Big Data extracts the semantic information from SNS and data mining is one of the big data technique. Especially, the general emotion analysis that expresses the collective intelligence of the masses is utilized using large and a variety of materials. In this paper, we propose the emotion prediction system architecture which extracts the significant keywords from social network paragraphs using n-gram and Korean morphological analyzer, and predicts the emotion using SVM and these extracted emotion features. The proposed system showed 82.25% more improved recall rate in average than previous systems and it will help extract the semantic keyword using morphological analysis.

• Journal of Aerospace System Engineering
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• v.17 no.4
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• pp.110-117
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• 2023

In this paper, the optimal placement of the rotary wing's communication and navigation antennas was evaluated by measuring their performance through ground simulations and flight tests. To select the mounting position of the communication and navigation antenna on the helicopter, after considering the shape and characteristics of the airframe, the radiation patterns, coupling analysis, equipment operation profiles, and antenna type analysis were performed for the aircraft-mounted antenna. Based on the analysis results, a procedure for sequentially performing voltage standing wave ratio (VSWR) measurement and antenna pattern test was established through ground and flight tests of the antenna. The systematic performance measurement method and procedure proposed in this paper were verified through ground and flight tests of the Light Armed Helicopter (LAH) system.