• Title/Summary/Keyword: Ontology-based

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Development of Ontology-based Intelligent Mold Design System (온톨로지 기반 지능형 금형 설계 시스템의 개발)

  • Lee, Sang-Hun;Kang, Mu-Jin;Eum, Kwang-Ho
    • Korean Journal of Computational Design and Engineering
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    • v.16 no.3
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    • pp.167-177
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    • 2011
  • This paper describes an ontology-based intelligent CAD system for injection mold design, which has been developed based on a commercial CAD system called Unigraphics and an ontological framework for representing the implicit design knowledge as well as the explicit based on the extended function-behavior-structure (FBS) engineering design model that includes the constraint. The system also provides various convenient solid modeling capabilities for mold design and the design process modeling capability that facilitates mold redesign process.

Context-Awareness for Location Based-Service for Ubiquitous Learning with underlying Principles of Ontology, Constructivism, Artificial Intelligence

  • Gelogo, Yvette;Kim, Hye-jin
    • International Journal of Internet, Broadcasting and Communication
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    • v.4 no.2
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    • pp.7-11
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    • 2012
  • In this paper, we defined constructivism and ontology theory and associate it in ubiquitous learning. The typical ubiquitous learning involving the Context Aware Intelligent system was presented. Also the Architecture for learning environment including the key idea and technical concept is being presented in this paper. Guided with these principles and with the advancement of information and communication technology the context-awareness based on Artificial intelligence for Location based Service for ubiquitous Learning was conceptualized.

an Automatic Transformation Process for Generating Multi-aspect Social IoT Ontology (다면적 소셜 IoT 도메인 온톨로지 생성을 위한 온톨로지 스키마 변환 프로세스)

  • Kim, SuKyung;Ahn, KeeHong;Kim, GunWoo
    • Smart Media Journal
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    • v.3 no.3
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    • pp.20-25
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    • 2014
  • This research proposes a concept of multi-aspect Social IoT platform that enables human, machine and service to communicate smoothly among them, as well as a means of an automatic process for transforming exiting domain knowledge representation to generic ontology representation used in the platform. Current research focuses on building a machine-based service interoperability using sensor ontology and device ontology. However, to the best of our knowledge, the research on building a semantic model reflecting multi-aspects among human, machine, and service seems to be very insufficient. Therefor, in the research we first build a multi-aspect ontology schema to transform the representation used in each domain as a part of IoT into ontology-based representation, and then develop an automatic process of generating multi-aspect IoT ontology from the domain knowledge based on the schema.

Comparability and uniformity of ontology for automated information integration of parts (부품 라이브러리의 자동 정보 통합을 위한 온톨로지의 비교 가능성과 균질성 확보)

  • Cho Joonmyun;Han Soonhung;Kim Hyun
    • The KIPS Transactions:PartD
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    • v.12D no.3 s.99
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    • pp.365-374
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    • 2005
  • The B2B electronic product commerce needs intermediary system to provide an integrated interface for the parts libraries of multiple suppliers. However, it is difficult to automatically integrate the parts libraries because they are heterogeneous. Existing ontology-based approaches show a limited functionality of automated integration of information because Dey can not prevent ontologies from being modeled in different ways, so that the inter-ontology mappings to resolve the heterogeneity become complicated and arbitrary. In order to overcome such problems this paper proposes an ontology modeling framework for parts libraries based on the Guarino's theory of upper ontology. The framework provides knowledge modeling primitives which have explicit formal meanings and modeling principles based on ontological natures. Using the framework, ontology developers can model the knowledge of parts libraries systematically and consistently, so that the resulting ontologies become comparable and uniform and the ontology merging algorithm for the automated information integration can be easily developed.

The Expert Search System using keyword association based on Multi-Ontology (멀티 온톨로지 기반의 키워드 연관성을 이용한 전문가 검색 시스템)

  • Jung, Kye-Dong;Hwang, Chi-Gon;Choi, Young-Keun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.1
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    • pp.183-190
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    • 2012
  • This study constructs an expert search system which has a mutual cooperation function based on thesis and author profile. The proposed methodology is as follows. First, we propose weighting method which can search a keyword and the most relevant keyword. Second, we propose a method which can search the experts efficiently with this weighting method. On the preferential basis, keywords and author profiles are extracted from the papers, and experts can be searched through this method. This system will be available to many fields of social network. However, this information is distributed to many systems. We propose a method using multi-ontology to integrate distributed data. The multi-ontology is composed of meta ontology, instance ontology, location ontology and association ontology. The association ontology is constructed through analysis of keyword association dynamically. An expert network is constructed using this multi-ontology, and this expert network can search expert through association trace of keyword. The expert network can check the detail area of expertise through the research list which is provided by the system.

Semi Automatic Ontology Generation about XML Documents

  • Gu Mi Sug;Hwang Jeong Hee;Ryu Keun Ho;Jung Doo Yeong;Lee Keum Woo
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.730-733
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    • 2004
  • Recently XML (eXtensible Markup Language) is becoming the standard for exchanging the documents on the web. And as the amount of information is increasing because of the development of the technique in the Internet, semantic web is becoming to appear for more exact result of information retrieval than the existing one on the web. Ontology which is the basis of the semantic web provides the basic knowledge system to express a particular knowledge. So it can show the exact result of the information retrieval. Ontology defines the particular concepts and the relationships between the concepts about specific domain and it has the hierarchy similar to the taxonomy. In this paper, we propose the generation of semi-automatic ontology based on XML documents that are interesting to many researchers as the means of knowledge expression. To construct the ontology in a particular domain, we suggest the algorithm to determine the domain. So we determined that the domain of ontology is to extract the information of movie on the web. And we used the generalized association rules, one of data mining methods, to generate the ontology, using the tag and contents of XML documents. And XTM (XML Topic Maps), ISO Standard, is used to construct the ontology as an ontology language. The advantage of this method is that because we construct the ontology based on the terms frequently used documents related in the domain, it is useful to query and retrieve the related domain.

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Intelligent Healthcare Service Provisioning Using Ontology with Low-Level Sensory Data

  • Khattak, Asad Masood;Pervez, Zeeshan;Lee, Sung-Young;Lee, Young-Koo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.11
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    • pp.2016-2034
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    • 2011
  • Ubiquitous Healthcare (u-Healthcare) is the intelligent delivery of healthcare services to users anytime and anywhere. To provide robust healthcare services, recognition of patient daily life activities is required. Context information in combination with user real-time daily life activities can help in the provision of more personalized services, service suggestions, and changes in system behavior based on user profile for better healthcare services. In this paper, we focus on the intelligent manipulation of activities using the Context-aware Activity Manipulation Engine (CAME) core of the Human Activity Recognition Engine (HARE). The activities are recognized using video-based, wearable sensor-based, and location-based activity recognition engines. An ontology-based activity fusion with subject profile information for personalized system response is achieved. CAME receives real-time low level activities and infers higher level activities, situation analysis, personalized service suggestions, and makes appropriate decisions. A two-phase filtering technique is applied for intelligent processing of information (represented in ontology) and making appropriate decisions based on rules (incorporating expert knowledge). The experimental results for intelligent processing of activity information showed relatively better accuracy. Moreover, CAME is extended with activity filters and T-Box inference that resulted in better accuracy and response time in comparison to initial results of CAME.

Integration with External Information Using Ontology for Rural Amenity Resources Information Service (농촌어메니티자원 정보서비스를 위한 Ontology를 활용한 외부정보 통합방안)

  • Lee, Ji-Min;Lee, Jeong-Jae
    • Journal of Korean Society of Rural Planning
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    • v.12 no.4 s.33
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    • pp.53-61
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    • 2006
  • Rural amenity resources consist of natural, cultural and social resources. Some of resources have been surveyed in other institutes and organizations and information system about these resources has been constructed. Integrating with information of existing system or database is helpful to produce useful rural amenity resources information to users. This integration of distributed information is based on semantic integration. In this paper, we used ontology for semantic integration and introduced the method of external information integration using ontology. We designed ontology table to represent ontology in database and integrated distributed information using ontology. To examine the improvement of information service efficiency and the applicability, rural amenity resources information and tourist attraction information database were constructed and integrated. Also, the information service efficiency with information integration was evaluated using recall ratio and compared to the information service efficiency without information integration.

Sharing CAD Models Based on Feature Ontology of Commands History

  • Seo, Tae-Sul;Lee, Yoon-Sook;Cheon, Sang-Uk;Han, Soon-Hung;Patil, Lalit;Dutta, Debasish
    • International Journal of CAD/CAM
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    • v.5 no.1
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    • pp.39-47
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    • 2005
  • Different CAx systems are being utilized throughout the product lifecycle due to the practical reasons in the supply chain and design processes. One of the major problems facing enterprises of today is how to share and exchange data among heterogeneous applications. Since different software applications use different terminologies, it is difficult to share and exchange the product data with internal and external partners. This paper presents a method to enhance the CAD model interoperability based on feature ontology. The feature ontology has been constructed based on the feature definition of modeling commands of CAD systems. A method for integration of semantic data has been proposed, implemented, and tested with two commercial CAD systems.

A Multi-Agent Improved Semantic Similarity Matching Algorithm Based on Ontology Tree (온톨로지 트리기반 멀티에이전트 세만틱 유사도매칭 알고리즘)

  • Gao, Qian;Cho, Young-Im
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.11
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    • pp.1027-1033
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    • 2012
  • Semantic-based information retrieval techniques understand the meanings of the concepts that users specify in their queries, but the traditional semantic matching methods based on the ontology tree have three weaknesses which may lead to many false matches, causing the falling precision. In order to improve the matching precision and the recall of the information retrieval, this paper proposes a multi-agent improved semantic similarity matching algorithm based on the ontology tree, which can avoid the considerable computation redundancies and mismatching during the entire matching process. The results of the experiments performed on our algorithm show improvements in precision and recall compared with the information retrieval techniques based on the traditional semantic similarity matching methods.