• 대한산업공학회지
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• 제23권1호
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• pp.95-113
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• 1997

This paper outlines a framework for a diagnosis of a complex system with uncertain information. Sensor validation ploys a vital role in the ability of the overall system to correctly determine the state of a system monitored by imperfect sensors. Here, emphases are put on the heuristic technology and post-processor for reasoning. Heuristic Sensor Validation (HSV) exploits deeper knowledge about parameter interaction within the plant to cull sensor faults from the data stream. Finally the modified probability distributions and validated data are used as input to the reasoning scheme which is the runtime version of the influence diagram. The output of the influence diagram is a diagnostic mapping from the symptoms or sensor readings to a determination of likely failure modes. Once likely failure modes are identified, a detailed diagnostic knowledge base suggests corrective actions to improve performance. This framework for a diagnostic expert system with sensor validation and reasoning under uncertainty applies in $HEATXPRT^{TM}$ a data-driven on-line expert system for diagnosing heat rate degradation problems in fossil power plants [1].

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2014년도 추계학술발표대회
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• pp.775-778
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• 2014

온톨로지(Ontology)는 시맨틱 웹 (Semantic Web) 구현 도구 중 하나로, 지식 개념을 의미적으로 연결하는 것에 쓰인다. 두 온톨로지 사이의 클래스 매핑은 온톨로지의 중요 연구 분야 중 하나이고, Unstructured, Semi-Strucutured Data가 증가함에 따라 스키마를 이용한 클래스 매핑은 한계를 갖게 되었다. 따라서 본 논문은 스키마를 이용하는 클래스 매핑이 아니라 온톨로지의 클래스에 존재하는 인스턴스의 정보를 활용하여 두 클래스간의 유사도를 측정하는 알고리즘을 제시한다. 이 알고리즘은 인스턴스 간에 측정한 유사도를 기반으로 서로 다른 두 온톨로지의 클래스 사이의 유사도를 측정하며, 전반적인 유사도는 높게 나오지 않았지만 모든 클래스 간의 매핑을 찾아내는 성능을 보였다.

• International Journal of Knowledge Content Development & Technology
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• 제13권1호
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• pp.75-100
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• 2023

With research data generation on the rise, Institutional Repositories (IR) are one of the tools to manage it. However, the variety of data practices across institutions, domains, communities, etc., often requires dedicated studies in order to identify the research data management (RDM) require- ments and mapping them to IR features to support them. In this study, we investigated the data practices for a few national universities in North Macedonia, including 110 participants from different departments. The methodology we adopted to this end enabled us to derive some of the key RDM requirements for a variety of data-related activities. Finally, we mapped these requirements to 6 features that our participants asked for in an IR solution: (1) create (meta)data and documentation, (2) distribute, share, and promote data, (3) provide access control, (4) store, (5) backup, and (6) archive. This list of IR features could prove useful for any university that has not yet established an IR solution.

• 정보관리연구
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• 제41권2호
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• pp.1-30
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• 2010

이 연구에서는 경제인문사회연구회 산하 19개 정부출연 연구기관이 2003년부터 2007년까지 5년동안 생산한 정책지식은 사회와 경제 분야의 10개 정책에 집중되고 있음을 확인하고, 연구기관들의 연구과제 유사성을 다차원축척법을 사용하여 표현하였다. 이 중 5대 정책에 대해 이슈의 생존주기 유형을 파악하고 정책지식의 생산량 추이와 비교함으로써 언론관심도와 정책지식의 생산 상관관계를 살펴보았다. 또한 정책지식의 문헌에서 추출한 핵심어를 동시출현단어 분석을 통해 각 정책을 구성하는 하위 주제를 파악하였으며, 정책지식 생산기관의�汰恝諛喚� 분석 결과,�泰逞╂岵막� 유사성을 갖는 기관들은 인용관계에서 있어서도 상호 선호하는 경향을 나타냄을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권11호
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• pp.5731-5754
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• 2019

In this paper, we redesign, implement, and evaluate ShareSafe (Based on SecGraph), an open-source secure graph data sharing/publishing platform. Within ShareSafe, we propose De-anonymization Quantification Module and Recommendation Module. Besides, we model the attackers' background knowledge and evaluate the relation between graph data privacy and the structure of the graph. To the best of our knowledge, ShareSafe is the first platform that enables users to perform data perturbation, utility evaluation, De-A evaluation, and Privacy Quantification. Leveraging ShareSafe, we conduct a more comprehensive and advanced utility and privacy evaluation. The results demonstrate that (1) The risk of privacy leakage of anonymized graph increases with the attackers' background knowledge. (2) For a successful de-anonymization attack, the seed mapping, even relatively small, plays a much more important role than the auxiliary graph. (3) The structure of graph has a fundamental and significant effect on the utility and privacy of the graph. (4) There is no optimal anonymization/de-anonymization algorithm. For different environment, the performance of each algorithm varies from each other.

• 한국주거학회논문집
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• 제25권2호
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• pp.63-70
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• 2014

The dependence on cars for urban mobility and the exponential increase in traffic and urban infrastructure to sustain traffic have lead to an encapsulated way of life, where the connection with the natural environment is much more reduced and programmed. In a previous study, a process based on estimating distances showed that children who move around their city by automobile do not appreciate their environment as a spatial continuum, but rather as a series of independent spaces that are reached by automobile or bus, thereby evidencing a different way of conceptualizing urban space in the light of different cognitive structures (Goluboff, Garc$\acute{i}$a-Mira, and Garc$\acute{i}$a-Font$\acute{a}$n, 2002). The present study is concerned with the process of understanding and knowledge of urban space, and contrasting the cognitive structure of different groups. The implications that this study may have for urban planning are discussed.

• Journal of Information Processing Systems
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• 제19권1호
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• pp.55-66
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• 2023

Community portraits can deeply explore the characteristics of community structures and describe the personalized knowledge needs of community users, which is of great practical significance for improving community recommendation services, as well as the accuracy of resource push. The current community portraits generally have the problems of weak perception of interest characteristics and low degree of integration of topic information. To resolve this problem, the reader community portrait method based on the thematic and timeliness characteristics of interest labels (UIT) is proposed. First, community opinion leaders are identified based on multi-feature calculations, and then the topic features of their texts are identified based on the LDA topic model. On this basis, a semantic mapping including "reader community-opinion leader-text content" was established. Second, the readers' interest similarity of the labels was dynamically updated, and two kinds of tag parameters were integrated, namely, the intensity of interest labels and the stability of interest labels. Finally, the similarity distance between the opinion leader and the topic of interest was calculated to obtain the dynamic interest set of the opinion leaders. Experimental analysis was conducted on real data from the Douban reading community. The experimental results show that the UIT has the highest average F value (0.551) compared to the state-of-the-art approaches, which indicates that the UIT has better performance in the smooth time dimension.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.661-668
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• 2022

Various lean design and construction methods such as target value design, pull planning, value stream mapping have successfully transformed the commercial building construction industry into achieving improved productivity, higher design and construction quality, and meeting the target values of construction projects. Considering the significant advantages of lean, the accelerated dissemination and adoption of lean methods and tools for construction is highly desirable. Currently, the lean design and construction body of knowledge is imparted primarily through publications and conferences. However, one of the most effective ways to impart this soft knowledge is through getting students and trainees involved in hands-on participatory games, which can quickly help them truly understand the concept and apply it to real-world problems. The COVID-19 Pandemic has raised an urgent need of developing virtual games that can be played simultaneously from various locations over the Internet, but these virtual games should be as effective as in-person games. This research develops an online 3D simulation game for Target Value Design that is as effective as in-person games or possibly better in terms of knowledge capture and retention and enjoyable environment and experience. The virtual game is tested on volunteers using feedback from pre-and post- simulation surveys to evaluate its efficacy.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.505-509
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• 2020

Twitter is a useful medium to grasp various damage situations that have occurred in society. However, it is a laborious task to spot damage-related topics according to time in the environment where information is constantly produced. This paper proposes a methodology of constructing a knowledge structure by combining the BERT-based classifier and the community detection techniques to discover the topics underlain in the damage information. The methodology consists of two steps. In the first step, the tweets are classified into the classes that are related to human damage, infrastructure damage, and industrial activity damage by a BERT-based transfer learning approach. In the second step, networks of the words that appear in the damage-related tweets are constructed based on the co-occurrence matrix. The derived networks are partitioned by maximizing the modularity to reveal the hidden topics. Five keywords with high values of degree centrality are selected to interpret the topics. The proposed methodology is validated with the Hurricane Harvey test data.

• 지능정보연구
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• 제12권2호
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• pp.33-48
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• 2006

의미 웹(Semantic Web)과 이에 대한 관련기술들은 웹을 통해 자유롭게 정보를 공유할 수 있는 새로운 지평을 마련해 주었다. 이를 토대로 온톨로지(Ontology)에 대한 연구 역시 활발히 진행되어 왔으며, 결과적으로 온톨로지는 여러 가지 측면에서 가시적인 성과들을 이룩해 낼 수 있었다. 의미 웹에 대한 기대가 고조되면서, 온톨로지는 많은 연구 학자들로부터 각광을 받는 분야로 떠오를 수 있었으며, 오늘날, 이러한 온톨로지에 대한 연구는 지식표현Knowledge-Representation)등과 같은 학술적인 단계에서 벗어나 전자상거래 분야까지 그 영역을 넓혀 나가고 있다. 그러나 일부에서는 이러한 온톨로지의 양산으로 인해 발생할 문제들에 대한 우려의 목소리가 적지 않다. 즉, 현재 온톨로지들은 서로간의 이질성으로 인해 그 효용 가치를 위협받고 있다는 것이다. 예를 들어, 현재 Yahoo나 DMOZ Open Directory(www.(dmoz.org)등으로부터 제공 중인 상품 카테고리의 경우, 시각적으로는 유사해 보일지 모르나 그들이 지닌 카테고리 구조라든지 사용된 용어 등을 살펴보면 상당한 차이점이 존재한다는 사실을 발견해 낼 수 있다. 따라서 현재 온톨로지가 지향하는 본래의 효용 가치를 극대화시키기 위해서는 이러한 이질성을 극복할 수 있는 방법론이 반드시 필요하다고 할 수 있다. 본 연구에서는 현재 온톨로지 분야에서 가장 커다란 이슈로 떠오르고 있는 정보통합에 대한 해결책을 제시해 보고자 한다. 정보통합이란, 서로 이질적인 프로그래밍 언어나 형식으로 이루어진 데이터들을 통합하여 요약한 형태로 제공하는 기술이라 정의 내릴 수 있다. 이러한 정보 통합의 대표적인 분야로 Merging, Alignment, Translation, Articulation을 들 수 있는데, 이 가운데, 본 연구에서는 "Ontology Alignment"에 대해 집중적으로 다루어 보고자 한다. 이와 더불어, 현재 의미 웹이 지향하는 대표적인 특성 중 하나로써 상호운영성을 꼽을 수 있다. 온톨로지 매핑(Ontology mapping)은 이러한 상호운영성을 지원하기 위한 대표적인 기술로써 각광을 받고 있다. 따라서 우리는 이러한 온톨로지 매핑에 대한 방법론을 쇼핑몰 환경에 적용함으로써 서로 이질적인 상품 카테고리로 구성된 두 쇼핑몰간의 상품에 대한 매핑 알고리즘(Mapping Algorithm)을 제안하고자 한다. 또한, 효용성 검증을 위하여 온톨로지 매핑에 있어 이미 효용성을 검증 받은 PROMPT와의 비교 분석도 수행하여 본다.