• Proceedings of the Korea Information Processing Society Conference
• /
• 2008.05a
• /
• pp.32-35
• /
• 2008

유비쿼터스 컴퓨팅 환경에서 시스템은 사용자의 상황을 인지하여 그 상황에 적합한 서비스를 자동으로 생성하고 그 환경에 존재하는 장치들을 사용하여 제공할 수 있어야 한다. 서비스를 수행하는 주체는 사용하려는 장치들의 상태 정보를 알고 있어야 하며, 그 서비스가 현재 환경에 적합한 서비스인지를 결정할 수 있어야 하며, 현재 환경에서 제공 가능한 서비스를 사용자가 원하는지 파악할 수 있어야 한다. 이처럼, 서비스를 수행함에 있어 장치, 사용자, 환경으로 구성된 공간 정보의 판독은 필수 불가결한 요소이다. 따라서, 새롭게 도입되는 서비스가 기존 공간 정보를 파악하기 위한 공용 환경 모델이 필요하다. 본 연구에서는 온톨로지를 사용한 환경 모델을 제안한다. 공간 안에 모든 시스템은 이 환경 모델을 통해 자신의 서비스를 수행하는 과정에서 필요한 상황 정보를 인지할 수 있고, 이는 보다 효율적인 개인화 서비스를 제공하기 위한 기반으로 사용될 수 있다.

• Journal of Korea Multimedia Society
• /
• v.8 no.5
• /
• pp.618-632
• /
• 2005

A framework for semantic annotation oi human motion sequences is proposed in this paper. Motion capture technology is widely used for manuiacturing animation since it produces high qualify character motion similar to the actual motion of the human body. However, motion capture has a significant weakness due to the lack of an industry wide standard for archiving and retrieving motion capture data. It is difficult for animators to retrieve the desired motion sequences from motion capture files as there is no semantic annotation on already captured motion data. Our goal is to improve the reusability of motion capture data. To archive our goal first, we propose a standard format for integrating different motion capture file formals. Our standard format is called MCML (Motion Capture Markup Language). It is a markup language based on XML (extensible Markup Language). The purpose of MCML is not only to facilitate the conversion or integration of different formats, but also to allow for greater reusability of motion capture data, through the construction of a motion database storing the MCML documents Second, we define motion ontologies that are used to annotate and semantically organize human motion sequences. This ontology-based approach provides the means for discovering and exploiting the information and knowledge surrounding motion capture data.

• Journal of KIISE:Software and Applications
• /
• v.32 no.3
• /
• pp.202-214
• /
• 2005

The semantic web is the web paradigm that represents not general link of documents but semantics and relation of document. In addition it enables software agents to understand semantics of documents. We propose a semantic search based on inference with ontologies, which has the following characteristics. First, our search engine enables retrieval using explicit ontologies to reason though a search keyword is different from that of documents. Second, although the concept of two ontologies does not match exactly, can be found out similar results from a rule based translator and ontological reasoning. Third, our approach enables search engine to increase accuracy and precision by using explicit ontologies to reason about meanings of documents rather than guessing meanings of documents just by keyword. Fourth, domain ontology enables users to use more detailed queries based on ontology-based automated query generator that has search area and accuracy similar to NLP. Fifth, it enables agents to do automated search not only documents with keyword but also user-preferable information and knowledge from ontologies. It can perform search more accurately than current retrieval systems which use query to databases or keyword matching. We demonstrate our system, which use ontologies and inference based on explicit ontologies, can perform better than keyword matching approach .

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.10 no.7
• /
• pp.1585-1600
• /
• 2009

The goal of Semantic Web is to provide efficient and effective semantic search and web services based on the machine-processable semantic information of web resources. Therefore, the process of creating and adding computer-understandable metadata for a variety of web contents, namely, semantic annotation is one of the fundamental technologies for the semantic web. Recently, in order to manage annotation metadata, direct approach for embedding metadata into the document is mainly used in semantic annotation. However, many semantic annotation tools for web documents have been mainly worked with HTML documents, and most of these tools do not support semantic search functionalities using the metadata. In this paper, based on these problems and previous works, we propose the Ontology-based Semantic Annotation tool(OSA) to efficiently support semantic annotation for web documents(such as HTML, PDF). We define a semantic annotation model that represents ontological-semantic information by using RDFS(RDF Schema). Based on XMP(eXtensible Metadata Platform) standard, the model is encoded directly into the document. By using OSA with XMP, user can perform semantic annotation on web documents which are able to keep compatibility for managing annotation metadata. Eventually, the integrated semantic annotation metadata can be used effectively in semantic search for a variety of web contents.

• Journal of KIISE:Computing Practices and Letters
• /
• v.13 no.3
• /
• pp.179-192
• /
• 2007

Based on ontologies, semantic Web services enable the discovery, selection, and composition. OWL-S is a do facto standard ontology for describing semantics of Web services. Due to the difficulty of the OWL-S grammar, the teaming curve for constructing OWL-S description manually can be steep. This paper presents an efficient method for generating OWL-S descriptions from UML diagrams, which are widely used for software design and development. The proposed method is based on UML profiles to generate an OWL-S ontology from sequence or activity diagrams, which represent the behavior of a business process. Specifically, an XMI file extracted from UML diagrams is transformed into an OWL-S description via an XSLT script. Experimental results with a large volume of UML diagrams show that the proposed method deals with the control flow of complex processes and is superior to previous methods.

• Journal of Intelligence and Information Systems
• /
• v.17 no.3
• /
• pp.43-61
• /
• 2011

In this research, we propose a dynamic decision making using social context based on ontology. Dynamic adaptation is adopted for the high qualified decision making, which is defined as creation of proper information using contexts depending on decision maker's state of affairs in ubiquitous computing environment. Thereby, the context for the dynamic adaptation is classified as a static, dynamic and social context. Static context contains personal explicit information like demographic data. Dynamic context like weather or traffic information is provided by external information service provider. Finally, social context implies much more implicit knowledge such as social relationship than the other two-type context, but it is not easy to extract any implied tacit knowledge as well as generalized rules from the information. So, it was not easy for the social context to apply into dynamic adaptation. In this light, we tried the social context into the dynamic adaptation to generate context-appropriate personalized information. It is necessary to build modeling methodology to adopt dynamic adaptation using the context. The proposed context modeling used ontology and cases which are best to represent tacit and unstructured knowledge such as social context. Case-based reasoning and constraint satisfaction problem is applied into the dynamic decision making system for the dynamic adaption. Case-based reasoning is used case to represent the context including social, dynamic and static and to extract personalized knowledge from the personalized case-base. Constraint satisfaction problem is used when the selected case through the case-based reasoning needs dynamic adaptation, since it is usual to adapt the selected case because context can be changed timely according to environment status. The case-base reasoning adopts problem context for effective representation of static, dynamic and social context, which use a case structure with index and solution and problem ontology of decision maker. The case is stored in case-base as a repository of a decision maker's personal experience and knowledge. The constraint satisfaction problem use solution ontology which is extracted from collective intelligence which is generalized from solutions of decision makers. The solution ontology is retrieved to find proper solution depending on the decision maker's context when it is necessary. At the same time, dynamic adaptation is applied to adapt the selected case using solution ontology. The decision making process is comprised of following steps. First, whenever the system aware new context, the system converses the context into problem context ontology with case structure. Any context is defined by a case with a formal knowledge representation structure. Thereby, social context as implicit knowledge is also represented a formal form like a case. In addition, for the context modeling, ontology is also adopted. Second, we select a proper case as a decision making solution from decision maker's personal case-base. We convince that the selected case should be the best case depending on context related to decision maker's current status as well as decision maker's requirements. However, it is possible to change the environment and context around the decision maker and it is necessary to adapt the selected case. Third, if the selected case is not available or the decision maker doesn't satisfy according to the newly arrived context, then constraint satisfaction problem and solution ontology is applied to derive new solution for the decision maker. The constraint satisfaction problem uses to the previously selected case to adopt and solution ontology. The verification of the proposed methodology is processed by searching a meeting place according to the decision maker's requirements and context, the extracted solution shows the satisfaction depending on meeting purpose.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.2
• /
• pp.237-243
• /
• 2011

Various standard terminologies in medical field are composed individually to different structure. Therefore, information on crosswalking between the terminologies is needed to combine and use the terminologies. Lots of mapping tools have been developed and used to create the information. However, since those tools deal with specific terminologies, the information is restrictly created. To overcome this problem, some tools have been developed, which perform mapping tasks by composing various terminologies. However, the tools also have difficulty of composing automatically the terminologies because the terminologies have different structures. Therefore, in this paper, we propose a method for composing and using the terminologies in the developed mapping system with keeping the original structure of the terminologies. In the proposed method, additional terminologies could be added on the mapping system and used by making metadata involving information on location and structure of the terminologies. And the mapping system could cope flexibly with the changes of the structure or context of the terminologies. Moreover, various types of mapping information could be defined and created in the system because mapping data are constructed as triplets in ontology. Therefore, the mapping data can be transformed and distributed in different formats such as OWL, RDF, and Excel. Finally, we confirmed the usefulness of the mapping system based on the proposed method through the experiments about creating mapping data.

• Proceedings of the Korean Information Science Society Conference
• /
• 2006.06b
• /
• pp.217-219
• /
• 2006

전체적인 관점으로 국가 과학기술 R&D를 조망하는 국가 과학기술 R&D 기반정보 온톨로지는 인력정보, 과제정보, 성과정보를 포함하며 여러 URI들과 연계된다. 본 논문에서는 기존의 단일 URI 체계가 아닌 시스템 적이고 다층적인 국가 과락기술 R&D 기반정보 온톨로지의 인스턴스 레벨에 필요한 다중 URI 관리 및 서비스 시스템을 구현한다. 본 시스템은 관리적인 측면에서 웹 인터페이스 기반 URI 등록과 조회를, 서비스 측면에서 URI 질의중심의 웹서비스를 제공한다. 기존 정보(KISTI의 KOI, 학술진흥재단의 부서 및 기관, 국가과학기술인력 종합정보시스템의 인력DB)와 연계를 기반으로 가용성 및 재사용성을 높이고 신규정보를 위한 URI 생성규칙을 제공함으로써 URI 관리 및 서비스 시스템 완성도를 높였다.

• The Journal of Society for e-Business Studies
• /
• v.14 no.4
• /
• pp.167-179
• /
• 2009

This paper introduces techniques to recommend standardized tags using tag ontology. Tag recommendation consists of TWCIDF and TWCITC; the former technique automatically tags a large quantity of already existing document groups, and the latter recommends tagging for new documents. Tag groups are created through several processes, including preprocessing, standardization using tag ontology, automatic tagging and defining ranks for recommendation. In the preprocessing process, in order to search semantic compound nouns, words are combined to establish basic word groups. In the standardization process, typographical errors and similar words are processed. As a result of experiments conducted on the basis of techniques presented in this paper, it is proved that real-time automatic tagging and tag recommendation is possible while guaranteeing the accuracy of tag recommendation.

• Journal of Digital Convergence
• /
• v.13 no.2
• /
• pp.153-158
• /
• 2015

Biologists are pursuing genetics related researches that can provide the core information to understand a certain cancer or inherent diseases. However, biological experimentations can produce different results by the difference of various elements or environments at the time of experimentation and/or difference of interpretations. Therefore, currently existing research results can possibly provide different information. These inconsistency can be found through integration of gene information. Biologists can save their time and efforts to find certain gene information if the gene information is integrated without inconsistency. An efficient gene integration and augmentation scheme of gene information generated through different researches is introduced in this paper.