• Title/Summary/Keyword: Knowledge representation

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Methodology for Extended Schema Representation in Database Integration

  • 김철호
    • Journal of the military operations research society of Korea
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    • v.23 no.2
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    • pp.85-102
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    • 1997
  • There have been several research efforts to support interoperability among multiple databases. In integrating multiple databases, we must resolve schema conflicts due to the heterogeneity in databases. To resolve these conflicts, not only meta-data for database schemas but also general knowledge expressing the real world meanings associated with the database schemas are required. This paper presents a uniform representation method for relational schema and general knowledge base that is composed, among other things, of concept hierarchy and thematic roles in relationship, using the knowledge representation language Lk. This representation method has a flexible descriptive power which facilitates concepts to be expressed at different levels of granularity and can describe knowledge expressed in Lk are used for input of the next step, such as conflict resolution and query processing of multiple database.

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Development of a Knowledge Representation Scheme and Diagnosis Mechanism for Heterogeneous Distributed Fault Diagnosis (이종분산 고장 진단을 위한 지식표현 방법 및 진단 방법의 개발)

  • 안영애;박종희
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.12
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    • pp.1687-1696
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    • 1995
  • An integrated fault diagnosis system for heterogeneous manufacturing environments is developed. This system has a contrast with existing diagnosis systems in the respect that they are mostly for diagnosing faults on individual machines. In addition to the usual (e.g., audio, electrical) diagnostic signals, the characteristics of products from the machines are considered as the unifying diagnostic parameters among heterogeneous machines in the diagnosis. The system is composed of a knowledge representation scheme and a diagnostic query processing mechanism. Its knowledge representation scheme allows the diagnostic knowledges from heterogeneous unit diagnostic systems to be uniformly expressed in terms of the causal relations among relevant data items. It is flexible in the sense that causes for one relation can be effects for another may be reflected on our knowledge representation scheme. The diagnosis mechanism is based on a probabilistic inferencing method. This probablistic diagnosis mechanism provides more general diagnosis than existing ones in that it accommodates multiple causes and takes complication among causes into account. These scheme and mechanism are applied to a typical example to demonstrate how our system works.

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Reconstructible design knowledge expression using Design DNA method (Design DNA 방법을 이용한 재구성 가능한 설계 지식의 표현)

  • 고희병;하성도;김태수;이수홍
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2003.06a
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    • pp.1-4
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    • 2003
  • Knowledge classification and expression of constructed knowledge have been main research issues in the field of knowledge representation. Constructed design knowledge of the former product loses its utility when new products with different structures are introduced to the market. In order to construct the design knowledge for a new product. designers need to reconstruct the design knowledge with new relationships. The design knowledge has been constructed with level trees, but it is difficult to rearrange the relations. Design DNA is proposed in this work in order to facilitate the rearrangement of design knowledge and give flexibility to knowledge structure. Design DNA is based on Layout-oriented domain knowledge and Function-oriented domain knowledge, which enables to generate new design knowledge that will result in new part geometries for given constraints on the part functions. Design DNA is applied to the design knowledge of lever system of the automatic transmission of passenger cars as an example.

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A Knowledge Representation Scheme Formalizing Spatio-Temporal Aspects of Dynamic Situations in Virtual Environments

  • Gebre, Haymanot Alalo;Choi, Jun Seong;Park, Jong Hee
    • International Journal of Contents
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    • v.11 no.1
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    • pp.21-30
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    • 2015
  • A simulated realistic virtual environment is inhabited by autonomous cyber-humans who play the roles of agents in events. A key element, which enables this realism, is the historical context formed by time and space. A knowledge-representation scheme, composed of both spatial and temporal aspects needed by the agent to respond to dynamically changing situations, is essential for the design of a realistic virtual agent. In this work, spatial and temporal aspects of dynamic situations in the virtual environment have been formalized as a key component of our knowledge-representation scheme. This scheme provides a mathematical framework to construct realistic virtual situations that change with time, and background knowledge for agents in the simulated environment to deduce new pieces of information and plan against changing situations.

Knowledge Representation for the Automatic Shutdown System in Boiler Plants (보일러 플랜트의 자동 Shutdown 시스템을 위한 지식표현)

  • 송한영;황규석
    • Journal of the Korean Society of Safety
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    • v.11 no.3
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    • pp.143-153
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    • 1996
  • Shutdown of boiler plants is a dynamic, complicated, and hazardous operation. Operational error is a major contributor to danserous situations during boiler plant shutdowns. It is important to develop an automatic system which synthesizes operating procedures to safely go from normal operation to complete shutdown. Knowledge representation for automatic shutdown of boiler plants makes use of the hierarchical, rule-based framework for heuristic knowledge, the semantic network, frame for process topology, and AI techniques such as rule matching, forward chaining, backward chaining, and searching. This knowledge representation and modeling account for the operational states, primitive operation devices, effects of their application, and planning methodology. Also, this is designed to automatically formulate subgoals, search for positive operation devices, formulate constraints, and synthesize shutdown procedures in boiler plants.

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Knowledge Conversion between Conceptual Graph Model and Resource Description Framework

  • Kim, Jin-Sung
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.1
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    • pp.123-129
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    • 2007
  • On the Semantic Web, the content of the documents must be explicitly represented through metadata in order to enable contents-based inference. In this study, we propose a mechanism to convert the Conceptual Graph (CG) into Resource Description Framework (RDF). Quite a large number or representation languages for representing knowledge on the Web have been established over the last decade. Most of these researches are focused on design of independent knowledge description. On the Semantic Web, however, a knowledge conversion mechanism will be needed to exchange the knowledge used in independent devices. In this study, the CG could give an entire conceptual view of knowledge and RDF can represent that knowledge on the Semantic Web. Then the CG-based object oriented PROLOG could support the natural inference based on that knowledge. Therefore, our proposed knowledge conversion mechanism will be used in the designing of Semantic Web-based knowledge representation and inference systems.

Multilayer Knowledge Representation of Customer's Opinion in Reviews (리뷰에서의 고객의견의 다층적 지식표현)

  • Vo, Anh-Dung;Nguyen, Quang-Phuoc;Ock, Cheol-Young
    • Annual Conference on Human and Language Technology
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    • 2018.10a
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    • pp.652-657
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    • 2018
  • With the rapid development of e-commerce, many customers can now express their opinion on various kinds of product at discussion groups, merchant sites, social networks, etc. Discerning a consensus opinion about a product sold online is difficult due to more and more reviews become available on the internet. Opinion Mining, also known as Sentiment analysis, is the task of automatically detecting and understanding the sentimental expressions about a product from customer textual reviews. Recently, researchers have proposed various approaches for evaluation in sentiment mining by applying several techniques for document, sentence and aspect level. Aspect-based sentiment analysis is getting widely interesting of researchers; however, more complex algorithms are needed to address this issue precisely with larger corpora. This paper introduces an approach of knowledge representation for the task of analyzing product aspect rating. We focus on how to form the nature of sentiment representation from textual opinion by utilizing the representation learning methods which include word embedding and compositional vector models. Our experiment is performed on a dataset of reviews from electronic domain and the obtained result show that the proposed system achieved outstanding methods in previous studies.

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A Methodology for Representation of Clinical Data in Oriental Medicine (한의학의 증상표현을 위한 방법론)

  • Park Kyung Mo;Park Jong Hyun
    • Journal of Physiology & Pathology in Korean Medicine
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    • v.16 no.5
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    • pp.845-850
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    • 2002
  • This paper suggest a methodology for representation of findings which can be called as signs and symptoms. A finding consists of unit signs and unit symptoms, and moreover findings which appear in one individual patient have so many different relationship each other. So, it is nat appropriate to list all of possible findings as medical standard or to fill findings as independent things in paper for medical record. We try to distinguish finding item from finding list, and suggest the methodology by which we can make finding list from finding items. That is, we suggest finding item[Concept], value types, relationship, logical operator, and syntax as a component of representation. And by using urinary symptom, we make the example for representation methodology. Finally, we mention the background knowledge, brief research process of related area.

A WF-KMS Framework on the Semantic Web (시맨틱 웹을 이용한 워크플로우 기반의 지식관리 시스템 프레임워크)

  • Kwon Hyung-Cheol;Choi Doug-Won;Lee Dong-Cheol
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.27 no.4
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    • pp.69-76
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    • 2004
  • A framework for knowledge management system has been explored which enables the semantic search of knowledge on the web. Knowledge representation by RDF and RDF schema enables machine cognition of knowledge documents. Dublin core was adopted for structured metadata representation. Thereby, it enables the CBR and rule based reasoning for intelligent knowledge retrieval. Grafting of the WFMS technique unto the KMS facilitates the effective utilization of process knowledge and creation of new knowledge.