• Journal of Internet Computing and Services
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• v.2 no.2
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• pp.71-93
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• 2001

Commonly to design a database system. a conceptual database has to be designed and then it is transformed into a logical database schema prior to building a target database system. This paper proposes a method which transforms a Temporal Entity-Relationship Model(TERM) into a Temporal Object-Oriented Model(TOOM) to build an efficient database schema. I formalize the time concept in view of object versioning and specify the constraints required during transformation procedure. The proposed transformation method contributes to getting the logical temporal data from the conceptual temporal events Without any loss of semantics, Compared to other approaches of supporting various properties, this approach is more general and efficient because it is the semantically seamless transformation method by using the orthogonality of types of objects, semantics of relationships and constraints over roles.

• Korean Journal of Cognitive Science
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• v.23 no.2
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• pp.133-164
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• 2012

Paul Churchland(1989) suggests the theory of representation from the results of cognitive biology and connectionist AI studies. According to the theory, our representations of the diverse phenomena in the world can be represented as the positions of phase state spaces with the actions of the neurons or of the assembly of neurons. He insists connectionist AI neural networks can have the semantical category systems to recognize the world. But Fodor and Lepore(1996) don't look the perspective bright. From their points of view, the Churchland's theory of representation stands on the base of Quine's holism, and the network semantics cannot explain how the criteria of semantical content similarity could be possible, and so cannot the theory. This thesis aims to excavate which one is the better between the perspective of the theory and the one of Fodor and Lepore's. From my understandings of state space theory of representation, artificial nets can coordinates the criteria of contents similarity by the learning algorithm. On the basis of these, I can see that Fodor and Lepore's points cannot penetrate the Churchlands' theory. From the view point of the theory, we can see how the future's artificial systems can have the conceptual systems recognizing the world. Therefore we can have the perspectives what cognitive scientists have to focus on.

• The Journal of Society for e-Business Studies
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• v.11 no.3
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• pp.35-51
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• 2006

Information visualization plays an important role to provide a conceptual comprehension of the information and should be adjusted and featured to reflect the characteristics of the domain to which it is applied. Product searching in e-Commerce is not an exception. In this paper, we present visualization techniques that are specified for effectively browsing the results of product searching. We considered visualization techniques including MapNet and Cluster Map and modified them to reflect the characteristics of the product domain. We consider two types of search queries: category searching and product property searching, and make it possible to include more detailed product semantics in their search criteria. We also provide a query refinement mechanism so that even users with rack of understanding the products may rewrite their queries for better results.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1342-1349
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• 2006

오늘날의 제품개발환경은 분산환경에 존재하는 다양한 역량을 가진 참여자들의 협업을 요구하고 있으며, 협업은 참여자들이 필요로 하는 제품개발관련 정보들의 실시간 교환을 지원할 수 있도록 제품정보 간 상호운용성 확보를 기반으로 한다. STEP으로 알려진 ISO 10303은 제품개발의 전체적인 라이프사이클에서 필요한 제품정보의 표현과 공유 및 교환을 위한 대표적인 표준이다. 하지만 STEP을 이용하기 위해서는 각 도메인이 표준인 STEP 모델에 기반하여 제품정보를 모델링 하여야 한다. 그러나 대부분의 도메인은 자신의 목적에 따라 특화된 모델을 정의하고 사용하기 때문에 도메인에 특화된 형태의 제품정보모델을 STEP 모델로 변환할 수 있는 추가적인 메커니즘이 필요하다. 즉, STEP은 참조모델보다는 모든 도메인에서 제품정보모델링을 위해 사용가능한 표준의 정의에 초점을 맞춘다. 그러므로 참조모델로서의 STEP을 기반으로 다양한 도메인 특화된 제품정보모델 간 상호운용성 확보를 지원하기 위하여 본 논문에서는 STEP 제품정보모델의 시맨틱스를 체계적으로 정의할 수 있도록 온톨로지 구축을 통한 컨셉추얼 모델링을 수행한다. 컨셉추얼 모델링은 STEP 모델에 정확하고 완전한 의미를 부여하여, 다양한 도메인 특화된 모델 사이의 상호운용성 확보를 지원하고 참조모델로서 STEP의 능력을 확장한다.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.202-209
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• 2007

Compound verbs in Korean show properties of both syntactic phrases and lexical items. Earlier studies of compound verbs have either assumed two homonymous types, i.e. one as a syntactic phrase and the other as a lexical item, or posited some sort of transformation from a syntactic phrase into a lexical item. In this paper, I show empirical and conceptual problems for earlier studies, and present an alternative account in terms of Talmy's (2000) theory of lexicalization. Unlike Talmy who proposed [Path] conflation into [MOVE] for Korean, I suggest several types of [Co-Event] conflation; e.g. [$_{Co-Event}$ Manner] conflation as in kwul-e-kata 'to go by rolling', [$_{Co-Event}$ Concomitance] conflation as in ttal-a-kata 'to follow', [$_{Co-Event}$ Concurrent Result] conflation as in cap-a-kata 'to catch somebody and go', etc. The present proposal not only places Korean compound verbs in a broader picture of cross-linguistic generalizations, but, when viewed from Jackendoff's (1997) productive vs. semi-productive morphology, provides a natural account for classifying the compounds that allow -se intervention from those that do not.

• Journal of the Korean Society for Library and Information Science
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• v.48 no.4
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• pp.91-113
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• 2014

Although social metadata has strengths in creating amount of user-contributed resource descriptions, its function is limited because of its non-systematic characteristics. This research proposed an alternative approach to semantic organization of social metadata. It analyzed the semantics of tags created in LibraryThing in order to provide bibliographic categories for describing information resources. Social information Architecture is adopted in generating the bibliographic categories so that social metadata framework can be constructed. This framework can provide the conceptual foundations for semantically organizing social metadata and is expected to be applied to the existing approaches to automatically organize social metadata.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.32-41
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• 2000

In this paper, we proposed a method which predict the verb by using the neural network in order to enhance communication rate in augmentative communication system for Korean language disorders. Each word is represented by an information vector according to syntax and semantics, and is positioned at the state space by being partitioned into various regions different from a dictionary-like lexicon. Conceptual similarity is realized through position in state space. When a symbol was pressed, we could find the word for the symbol at the position in the state space. In order to prevent verb prediction's redundancy according to input units, we predicted the verb after separating class using the neural network. In the result we can enhance $20\% communication rate in the restricted space

• Journal of the Korean Society for Library and Information Science
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• v.45 no.2
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• pp.185-207
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• 2011

In the current information environment, many approaches have been adopted to represent and organize information resources. Among these approaches, folksonomy using tags is now being used in knowledge representation and organization. Although it may be an efficient approach to overcome the limitations of previous approaches, there are several problems in assigning tags such as ambiguity, inconsistency, and polysemy that limit efficient information organization. This research proposes a conceptual framework for the control of semantics of tags through linking up with bibliographic records in order to maximize the efficiency and minimize the limitations of folksonomy tags.

• Journal of Digital Contents Society
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• v.9 no.2
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• pp.285-293
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• 2008

In Semantic Web, metadata and ontology for representing semantics and conceptual relationships of information resources are essential factors. RDF and RDF Schema are W3C standard models for describing metadata and ontology. Therefore, many studies to store and retrieve RDF and RDF Schema documents are required. In this paper, we focus on some results of analyzing available query patterns considering both RDF and RDF Schema and classify queries on RDF and RDF Schema into the three patterns. RDF and RDF Schema can be represented as graph models. So, we proposed some strategies to store and retrieve using the graph models of RDF and RDF Schema. We can retrieve entities that can be arrived from a certain class or property in RDF and RDF Schema without a loss of performance on account of multiple joins with tables.

• Journal of KIISE:Databases
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• v.35 no.2
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• pp.132-142
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• 2008

In biological domain, there exist a variety of protein analysis databases which have their own meaning toward the same target of protein. If we integrate these scattered heterogeneous data efficiently, we can obtain useful information which otherwise cannot be found from each original source. Reflecting the characteristics of biological data, each data source has its own syntax and semantics. If we describe these data through RDF(S) models, one of the Semantic Web standards, we can achieve not only syntactic but also semantic integration. In this paper, we propose a new concept of integration layer based on the RDF unified schema. As a conceptual model, we construct a unified schema focusing on the protein information; as a representational model, we propose a technique for the wrappers to aggregate necessary information from the relevant sources and dynamically generate RDF instances. Two example queries show that our integration layer succeeds in processing the integrated requests from users and displaying the appropriate results.