• Journal of Ship and Ocean Technology
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• 제9권3호
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• pp.33-42
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• 2005

As the networks connect the world, enterprises tend to move manufacturing activities into virtual spaces. Since different software applications use different data terminology, it becomes a problem to interoperate, interchange, and manage electronic data among heterogeneous systems. It is said that approximately one billion dollar has been being spent yearly in USA for product data exchange and interoperability. As commercial CAD systems have brought in the concept of design feature for the sake of interoperability, terminologies of design features need to be harmonized. In order to define design feature terminology for integration, knowledge about feature definitions of different CAD systems should be considered. STEP standard have attempted to solve this problem, but it defines only syntactic data representation so that semantic data integration is not possible. This paper proposes a methodology for integrating modeling features of CAD systems. We utilize the ontology concept to build a data model of design features which can be a semantic standard of feature definitions of CAD systems. Using feature ontology, we implement an integrated virtual database and a simple system which searches and edits design features in a semantic way.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권6호
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• pp.2022-2042
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• 2014

The term "big data" has recently gained widespread attention in the field of information technology (IT). One of the key challenges in making use of big data lies in finding ways to uncover relevant and valuable information. The high volume, velocity, and variety of big data hinder the use of solutions that are available for smaller datasets, which involve the manual interpretation of data. Semantic computing technologies have been proposed as a means of dealing with these issues, and with the advent of linked data in recent years, have become central to mainstream semantic computing. This paper attempts to uncover the state-of-the-art semantics-based approaches and tools that can be leveraged to enrich and enhance today's big data. It presents research on the latest literature, including 61 studies from 2011 to 2014. In addition, it highlights the key challenges that semantic approaches need to address in the near future. For instance, this paper presents cutting-edge approaches to ontology engineering, ontology evolution, searching and filtering relevant information, extracting and reasoning, distributed (web-scale) reasoning, and representing big data. It also makes recommendations that may encourage researchers to more deeply explore the applications of semantic technology, which could improve the processing of big data. The findings of this study contribute to the existing body of basic knowledge on semantics and computational issues related to big data, and may trigger further research on the field. Our analysis shows that there is a need to put more effort into proposing new approaches, and that tools must be created that support researchers and practitioners in realizing the true power of semantic computing and solving the crucial issues of big data.

• 전기전자학회논문지
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• 제12권4호
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• pp.217-224
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• 2008

This paper provides a framework for semantic correspondence of heterogeneous databases using self- organizing map. It solves the problem of overlapping between different databases due to their different schemas. Clustering technique using self-organizing maps (SOM) is tested and evaluated to assess its performance when using different kinds of data. Preprocessing of database is performed prior to clustering using edit distance algorithm, principal component analysis (PCA), and normalization function to identify the features necessary for clustering.

• 한국정보과학회논문지:데이타베이스
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• 제30권5호
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• pp.476-493
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• 2003

이동 컴퓨팅(mobile computing) 환경이 가지는 통신 대역의 협소함과 이동 기기의 에너지 제약 때문에 데이타 베이스 서버에서 다수의 이동 클라이언트로 데이타를 전달할 때는 브로드캐스트 (broadcast)가 효과적이다. 기존의 여러 가지 브로드캐스트 방법은 클라이언트의 데이타 접근 빈도(access frequency)를 이용하여 전송 스케줄을 정하거나, 데이타들의 시맨틱 관계(semantic relationship)를 이용하여 전송 스케줄을 결정하였다. 데이타의 접근 빈도만을 반영하는 경우 클라이언트들이 접근하는 데이타들의 의미적 관계를 고려하지 않으므로 클라이언트가 밀접한 시맨틱 관계를 갖는 데이타를 차례로 접근해야 하는 경우 오랜 시간 동안 무선 채널을 듣고 있어야 한다. 시맨틱 관계만을 반영하여 전송 스케줄을 작성하면, 클라이언트가 시맨틱 관계는 없으나 접근 빈도가 높은 특정 데이타를 자주 접근할 필요가 있는 경우, 클라이언트의 데이타 접근 시간이 길어지게 된다. 이 논문에서는 데이타 접근 빈도와 시맨틱 관계를 함께 반영하여 이동 클라이언트의 데이타 접근 시간을 개선한 효율적인 하이브리드 데이타 브로드캐스트 방법을 제안한다. 우리가 제안하는 하이브리드 브로드캐스트 방법은 데이타 접근 빈도에 의해 브로드캐스트 스케줄을 생성한 후, 스케줄 상 데이타 전송 위치를 시맨틱 관계에 따라 조정한다. 시뮬레이션을 통해 기존의 방법들과 성능을 비교 분석하여 우리의 방법이 효율적임을 보인다.

• Journal of Information Processing Systems
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• 제12권1호
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• pp.129-148
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• 2016

Acute myocardial infarction (AMI) is one of the three emergency diseases that require urgent diagnosis and treatment in the golden hour. It is important to identify the status of the coronary artery in AMI due to the nature of disease. Therefore, multi-modal medical images, which can effectively show the status of the coronary artery, have been widely used to diagnose AMI. However, the legacy system has provided multi-modal medical images with flat and unstructured data. It has a lack of semantic information between multi-modal images, which are distributed and stored individually. If we can see the status of the coronary artery all at once by integrating the core information extracted from multi-modal medical images, the time for diagnosis and treatment will be reduced. In this paper, we analyze semantic relations between multi-modal medical images based on coronary anatomy for AMI. First, we selected a coronary arteriogram, coronary angiography, and echocardiography as the representative medical images for AMI and extracted semantic features from them, respectively. We then analyzed the semantic relations between them and defined the convergence data model for AMI. As a result, we show that the data model can present core information from multi-modal medical images and enable to diagnose through the united view of AMI intuitively.

• 전자통신동향분석
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• 제37권6호
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• pp.74-83
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• 2022

Shannon and Weaver's semantic communication has been actively studied in recent years as a new communication method to provide intelligent mobile services without requiring more capacity, infrastructure, and energy, even with limited radio resources. Considered a breakthrough beyond the Shannon paradigm, semantic communication aims at successfully transmitting semantic information conveyed by a source rather than accurately receiving each symbol or bit, regardless of meaning. Thus, semantic communication can lead to knowledgeable systems that significantly reduce data traffic because the transmitter only transmits the necessary information related to a specific task. This study describes essential differences between existing and semantic communication, research trends related to semantic communication principles and theory, performance metrics of semantic communication, semantic communication system framework, and future research and development issues.

• 한국전자거래학회지
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• 제21권4호
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• pp.1-14
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• 2016

시멘틱 검색은 검색 사용자의 인지적 노력을 최소화하면서 사용자 질의의 문맥을 이해하여 의미에 맞는 문서를 정확히 찾아주는 기술이다. 아직 시멘틱 검색 기술은 온톨로지 또는 시멘틱 메타데이터 구축의 난제를 갖고 있으며 상용화 사례도 매우 미흡한 실정이다. 본 논문은 기존 시멘틱 검색 엔진의 한계를 극복하기 위하여 이전 연구에서 고안한 위키피디아 기반의 시멘틱 텐서공간모델을 활용하여 새로운 시멘틱 검색 기법을 제안한다. 제안하는 시멘틱 기법은 문서 집합에 출현하는 '단어'가 텐서공간모델에서 '문서-개념'의 2차 텐서(행렬), '개념'은 '문서-단어'의 2차 텐서로 표현된다는 성질을 이용하여 시멘틱 검색을 위해 요구되는 온톨로지 구축의 필요성을 없앤다. 그럼에도 불구하고, OHSUMED, SCOPUS 데이터셋을 이용한 성능평가를 통해 제안 기법이 벡터공간모델에서의 기존 검색 기법보다 우수함을 보인다.

• 한국IT서비스학회지
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• 제13권2호
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• pp.133-149
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• 2014

It is unavoidable to provide products that meet customers' needs and wants so that firms may survive under the competition in this globalized market. This paper focuses on how to provide levels for attributes that compse product so that firms may give the best products to customers. In particular, its main issue is how to determine common attributes and the others with their appropriate levels to maximize firms' profits, and how to construct a decision support system to ease decision makers' decisons about optimal common attribute selection using the Semantic Web and SWCL technologies. Parameter data in problems and the relationships in the data are expressed in an ontology data model and a set of constraints by using the Semantic Web and SWCL technologies. They generate a quantitative decision making model through the automatic process in the proposed system, which is fed into the solver using the Logic-based Benders Decomposition method to obtain an optimal solution. The system finally provides the generated solution to the decision makers. This presentation suggests the opportunity of the integration of the proposed system with the broader structured data network and other decision making tools because of the easy data shareness, the standardized data structure and the ease of machine processing in the Semantic Web technology.

• ETRI Journal
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• 제42권2호
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• pp.239-246
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• 2020

Recently, Linked Open Data has become a large set of knowledge bases. Therefore, the need to query Linked Data using question answering (QA) techniques has attracted the attention of many researchers. A QA system translates natural language questions into structured queries, such as SPARQL queries, to be executed over Linked Data. The two main challenges in such systems are lexical and semantic gaps. A lexical gap refers to the difference between the vocabularies used in an input question and those used in the knowledge base. A semantic gap refers to the difference between expressed information needs and the representation of the knowledge base. In this paper, we present a novel method using an ontology lexicon and dependency parse trees to overcome lexical and semantic gaps. The proposed technique is evaluated on the QALD-5 benchmark and exhibits promising results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권8호
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• pp.2704-2719
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• 2022

Lately, neo-Chinese style furniture has been frequently noticed by product design professionals for the big part it played in promoting traditional Chinese culture. This article is an attempt to use big data semantic analysis method to provide effective design research method for neo-Chinese furniture design. By using big data mining program TEXTOM for big data collection and analysis, the data obtained from typical websites in a set time period will be sorted and analyzed. On the basis of "neo-Chinese furniture" samples, key data will be compared, classification analysis of overall data, and horizontal analysis of typical data will be performed by the methods of word frequency analysis, connection centrality analysis, and TF-IDF analysis. And we tried to summarize according to the related views and theories of the design. The research results show that the results of data analysis are close to the relevant definitions of design. The core high-frequency vocabulary obtained under data analysis, such as popular, furniture, modern, etc., can provide a reasonable and effective focus of attention for the designs. The result obtained through the systematic sorting and summary of the data can be a reliable guidance in the direction of our design. This research attempted to introduce related big data mining semantic analysis methods into the product design industry, to supply scientific and objective data and channels for studies on design, and to provide a case on the practical application of big data analysis in the industry.