• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.208-210
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• 2004

오늘날 인터넷상에서 존재하는 않은 정보들은 다양한 사용자의 개인 특성에 안게 새로운 정보의 지식으로 제공되어지기를 원한다. 기존의 연구는 단일 학술 기법을 통해 정보를 추출했으나 사용자에게 보다 의미 있는 정보를 제공하기 위해 다중 전략 학습 기법인 PMSL(Personalized Multi-Strategy Learning) 모듈 시스템을 제안하고자 한다. PMSL 모듈은 인터넷의 정보를 여과하여 필터링하고, 사용자 개인화의 키워드를 중심으로 연관된 객체를 추출한다. 이때 연관된 객체 추출시 대용량 데이터에서 시간적, 공간적면에서 효율적인 연관 탐색 기법인 Fp-Tree와 Fp-Growth 알고리즘을 적용시킴으로 결과의 효율성을 높이고자 하였으며, 연관규칙의 문제점을 보완하기 위해 가중치 기법인 TF＊IDF 학습 기법을 적용시켰다. PMSL 모듈을 실행한 결과 기존 학습 기법에 비해 보다 더 의미 있는 연관 지식을 추출하게 되었다.

• Journal of KIISE:Databases
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• v.31 no.5
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• pp.492-504
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• 2004

Recently, as growing of interest for LBS(location-based services) techniques, lots of works on moving objects that continuously change their information over time, have been performed briskly. Also, researches for NN(nearest neighbor) query which has often been used in LBS, are progressed variously However, the results of conventional NN Query processing techniques may be invalidated as the query and data objects move. Therefore, they are usually meaningless in moving object management system such as LBS. To solve these problems, in this paper we propose a new nearest neighbor query processing technique, called CTNN, which is possible to meet accurate and continuous query processing for moving objects. Our techniques include an Approximate CTNN(ACTNN) technique, which has quick response time, and an Exact CTNN(ECTNN) technique, which makes it possible to search nearest neighbor objects accurately. In order to evaluate the proposed techniques, we experimented with various datasets. Experimental results showed that the ECTNN technique has high accuracy, but has a little low performance for response time. Also the ACTNN technique has low accuracy comparing with the ECTNN, but has quick response time The proposed techniques can be applied to navigation system, traffic control system, distribution information system, etc., and specially are most suitable when both data and query are moving objects and when we already know their trajectory.

• Journal of Internet Computing and Services
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• v.10 no.5
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• pp.79-93
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• 2009

For developing the location based service which is individualized and specialized according to the characteristic of the users, the spatio-temporal pattern mining for extracting the meaningful and useful patterns among the various patterns of the mobile object on the spatio-temporal area is needed. Thus, in this paper, as the practical application toward the development of the location based service in which it is able to apply to the real life through the pattern mining from the huge historical data of mobile object, we are proposed STOMP(using Frequency of sequence and Weight) that is the new mining method for extracting the patterns with spatial and temporal constraint based on the problems of mining the optimal moving pattern which are defined in STOMP(F)[25]. Proposed method is the pattern mining method compositively using weighted value(weights) (a distance, the time, a cost, and etc) for our previous research(STOMP(F)[25]) that it uses only the pattern frequent occurrence. As to, it is the method determining the moving pattern in which the pattern frequent occurrence is above special threshold and the weight is most a little bit required among moving patterns of the object as the optimal path. And also, it can search the optimal path more accurate and faster than existing methods($A^*$, Dijkstra algorithm) or with only using pattern frequent occurrence due to less accesses to nodes by using the heuristic moving history.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.535-537
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• 2000

인체 장기의 내부 벽면을 관찰하기 위하여 사용된 내시경 검사 기법은 내시경을 삽입하고, 질병 부위를 찾는 과정에서 환자에게 고통을 유발시키고, 정확한 진단을 내리기 위해서는 검사자의 오랜 경험과 숙달을 필요로 한다. 그러므로 각종 의료 영상을 기반으로 한 가상 내시경 시스템에 대한 연구와 개발이 요구된다. 본 논문에서는 초음파 영상을 기반으로 하여 병변 부위의 3차원 영상을 생성하고, 탐색하는 시스템을 제안한다. 우선 획득된 초음파 영상으로부터 장기에 대한 윤곽선 정보를 얻기 위하여, 초음파 영상에 대한 전처리 작업과 분할 작업을 수행하였고, 추출된 윤곽선 정보를 기반으로 3차원 표면 모델을 생성하였다. 3차원 표면 모델은 VRML 2.0 형식의 3차원 객체로 자동 변환되어 일반 VRML Plug-in viewer 및 자바 제어 모듈을 이용하여 3차원 장기 모델에 대한 탐색을 가능하도록 하였다.

• Proceedings of the Korea Multimedia Society Conference
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• 1998.04a
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• pp.400-405
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• 1998

현재 네트워크 환경과 컴퓨터시스템 환경에서의 고장 또는 장애에 의해서 통신이 않되는 경우에는 사용자들의 불편이 가중되고 있는 실정이다. 네트워크의 확장으로 인하여 네트워크를 관리하기 위한 도구들이 개발되어 왔다. 이 문제를 해결하기 위해서 본 논문에서는 네트워크 및 컴퓨터시스템 환경에서 발생하는 장애에 대한 원인 분석과 이에 따른 장애의 진단과 처치를 위하여 전문가시스템의 기법을 도입하였다. 장애의 원인을 탐색하기 위하여서는 추론기관과 지식베이스를 구성하였으며, 장애요인에 대한 지식은 장애를 하나의 객체로 하는 기법을 사용하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.800-802
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• 2003

이 논문에서는 웹 기반의 하이퍼미디어 교육시스템에서 이산 확률 분포 함수와 사용자 프로파일 기반의 동적 적응 모델을 제안하였다. 이 모델은 응용 영역을 동적 적응 객체의 가중치 방향성 그래프로 표현하며 사용자 행위를 이산 확률 함수를 동적으로 구축하는 접근 방식을 이용하여 모델링 한다. 제안한 확률적 해석은 웹 미디어 구조에서 사용자의 탐색 행위를 추적하여 사용자 행위에 대한 잠재적 속성을 나타내는데 사용될 수 있다. 이러한 접근 방식은 사용자에게 가장 알맞은 프로파일을 동적으로 할당할 수 있다.

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.537-546
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• 2014

In this paper, we propose a method to detect interesting objects in inaccessible areas using high resolution satellite images. We define the interesting objects as a set of objects which have conceptually similar image patterns, not having exact sizes or shapes. In this paper, we developed a learning and classifier of Support Vector Machine (SVM) that extracts characteristic data for inputted images using Histogram of Gradients (HOG) feature and detects similar objects in other images using the characteristic data. As automatic search of interesting objects in our proposed method, we identify that our method provides reduced time and efforts for manual searching similar objects.

• Journal of the Korean Society for information Management
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• v.29 no.4
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• pp.123-142
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• 2012

To develop an intelligent search engine to help users retrieve information effectively, various methods, such as Semantic Web, have been used, An effective retrieval method of such methods uses ontology technology. In this paper, we built National R&D ontology after analyzing National R&D Information in NTIS and then implemented National R&D Knowledge Map to represent and retrieve information of the relationship between object and subject (project, human information, organization, research result) in R&D Ontology. In the National R&D Knowledge Map, center-node is the object selected by users, node is subject, subject's sub-node is user's favorite query in National R&D ontology after analyzing the relationship between object and subject. When a user selects sub-node, the system displays the results from inference engine after making query by SPARQL in National R&D ontology.

• The KIPS Transactions:PartD
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• v.10D no.7
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• pp.1103-1114
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• 2003

Currently, one of the most critical issues in developing the service support system for various spatio-temporal applications is the discoverying of meaningful knowledge from the large volume of moving object data. This sort of knowledge refers to the spatiotemporal moving pattern. To discovery such knowledge, various relationships between moving objects such as temporal, spatial and spatiotemporal topological relationships needs to be considered in knowledge discovery. In this paper, we proposed an efficient method, MPMine, for discoverying spatiotemporal moving patterns. The method not only has considered both temporal constraint and spatial constrain but also performs the spatial generalization using a spatial topological operation, contain(). Different from the previous temporal pattern methods, the proposed method is able to save the search space by using the location summarization and generalization of the moving object data. Therefore, Efficient discoverying of the useful moving patterns is possible.

• Spatial Information Research
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• v.14 no.3 s.38
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• pp.299-319
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• 2006

This research is primarily intended to investigate the potential of estimating green space threshold in terms of total volume control using degradation trends of green space derived from remote sensing and GIS. An empirical study for a case study site was conducted to demonstrate how a standard remote sensing and GIS technology can be used to assist in estimating the total control volume for green space in terms of area-wide information, spatial resolution and change detection etc. Guidelines for a replicable methodology are presented to provide a strong theoretical basis for the standardization of factors involved in the estimation of the green space threshold; the meaningful definition of land mosaic, redefinition of degradation trends for green space. It was demonstrated that the degradation trends of green space could be used effectively as an indicator to restrict further development of the sites since the visual maps generated from remote sensing and GIS can present area-wide visual evidences by permanent record. It is anticipated that this research output could be used as a valuable reference to support more scientific and objective decision-making in introducing aggregate control of green space.