• Title/Summary/Keyword: task-based ontology

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Ubiquitous Operation Composition based on Task (태스크 기반의 유비쿼터스 오퍼레이션 조합)

  • Hwang, Yun-Young;Lee, Kyu-Chul
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.5
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    • pp.519-524
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    • 2010
  • In this paper, we will introduce our approach for composing operation based on user tasks. It is based on Service Component Architecture (SCA). In addition, we developed ontology based on OWL and the MIT process handbook, called u-TO(universal task ontology), which can be used for users describing and specifying semantically their needs. We represent the hierarchy of tasks, and classify tasks according to views in u-TO. It aims at facilitating the modeling of complex demands or systems without regarding details of technical aspects of underlying infrastructure.

Ontology-Based Process-Oriented Knowledge Map Enabling Referential Navigation between Knowledge (지식 간 상호참조적 네비게이션이 가능한 온톨로지 기반 프로세스 중심 지식지도)

  • Yoo, Kee-Dong
    • Journal of Intelligence and Information Systems
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    • v.18 no.2
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    • pp.61-83
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    • 2012
  • A knowledge map describes the network of related knowledge into the form of a diagram, and therefore underpins the structure of knowledge categorizing and archiving by defining the relationship of the referential navigation between knowledge. The referential navigation between knowledge means the relationship of cross-referencing exhibited when a piece of knowledge is utilized by a user. To understand the contents of the knowledge, a user usually requires additionally information or knowledge related with each other in the relation of cause and effect. This relation can be expanded as the effective connection between knowledge increases, and finally forms the network of knowledge. A network display of knowledge using nodes and links to arrange and to represent the relationship between concepts can provide a more complex knowledge structure than a hierarchical display. Moreover, it can facilitate a user to infer through the links shown on the network. For this reason, building a knowledge map based on the ontology technology has been emphasized to formally as well as objectively describe the knowledge and its relationships. As the necessity to build a knowledge map based on the structure of the ontology has been emphasized, not a few researches have been proposed to fulfill the needs. However, most of those researches to apply the ontology to build the knowledge map just focused on formally expressing knowledge and its relationships with other knowledge to promote the possibility of knowledge reuse. Although many types of knowledge maps based on the structure of the ontology were proposed, no researches have tried to design and implement the referential navigation-enabled knowledge map. This paper addresses a methodology to build the ontology-based knowledge map enabling the referential navigation between knowledge. The ontology-based knowledge map resulted from the proposed methodology can not only express the referential navigation between knowledge but also infer additional relationships among knowledge based on the referential relationships. The most highlighted benefits that can be delivered by applying the ontology technology to the knowledge map include; formal expression about knowledge and its relationships with others, automatic identification of the knowledge network based on the function of self-inference on the referential relationships, and automatic expansion of the knowledge-base designed to categorize and store knowledge according to the network between knowledge. To enable the referential navigation between knowledge included in the knowledge map, and therefore to form the knowledge map in the format of a network, the ontology must describe knowledge according to the relation with the process and task. A process is composed of component tasks, while a task is activated after any required knowledge is inputted. Since the relation of cause and effect between knowledge can be inherently determined by the sequence of tasks, the referential relationship between knowledge can be circuitously implemented if the knowledge is modeled to be one of input or output of each task. To describe the knowledge with respect to related process and task, the Protege-OWL, an editor that enables users to build ontologies for the Semantic Web, is used. An OWL ontology-based knowledge map includes descriptions of classes (process, task, and knowledge), properties (relationships between process and task, task and knowledge), and their instances. Given such an ontology, the OWL formal semantics specifies how to derive its logical consequences, i.e. facts not literally present in the ontology, but entailed by the semantics. Therefore a knowledge network can be automatically formulated based on the defined relationships, and the referential navigation between knowledge is enabled. To verify the validity of the proposed concepts, two real business process-oriented knowledge maps are exemplified: the knowledge map of the process of 'Business Trip Application' and 'Purchase Management'. By applying the 'DL-Query' provided by the Protege-OWL as a plug-in module, the performance of the implemented ontology-based knowledge map has been examined. Two kinds of queries to check whether the knowledge is networked with respect to the referential relations as well as the ontology-based knowledge network can infer further facts that are not literally described were tested. The test results show that not only the referential navigation between knowledge has been correctly realized, but also the additional inference has been accurately performed.

Ontology-based Information Management for Data and Task Migration in Collaborative Work

  • Huq, Mohammad Rezwanul;Lee, Young-Koo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2007.05a
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    • pp.14-15
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    • 2007
  • Now-a-days, data and task migration in collaborative work provides enormous facilities to users. Here, we propose an ontology-based information management scheme to facilitate data and task migration in collaborative work. This ontologybased model will help us to organize huge information (e.g. device status, runtime state etc.) efficiently.

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Ontology-based Safety Risk Interactions Analysis for Supporting Pre-task Planning

  • Tran, Si Van-Tien;Lee, Doyeop;Pham, Trang Kieu;Khan, Numan;Park, Chansik
    • International conference on construction engineering and project management
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    • 2020.12a
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    • pp.96-102
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    • 2020
  • The construction industry remains serious accidents, injuries, and fatalities due to it's unique, dynamic, and temporary nature. On workplace sites, Safety pre-task planning is one of the efforts to minimize injuries and help construction personnel to identify potential hazards. However, the working conditions are complicated. Many activities, including tasks or job steps, are executing at the same time and place. It may lead to an increase in the risks from simultaneous tasks. This paper contributes to addressing this issue by introducing a safety risk interaction analyzing framework. To accomplish this objective, accident reports of the Occupational Safety and Health Administration (OSHA) are investigated. The pairs of task incompatibility, which have time-space conflicts and lead to incidents, are found. Ontology technology is applied to build the risk database, in which the information is acquired, structuralized. The proposed system is expected to improve pre-task planning efficiency and relieve the burdens encountered by safety managers. A user scenario is also discussed to demonstrate how the ontology supports pre-task planning in practice.

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Task-Based Ontology of Problem Solving Adapters for Developing Intelligent Systems

  • Ko, Jesuk;Kitjongthawonkul, Somkiat
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.4 no.3
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    • pp.353-360
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    • 2004
  • In this paper we describe Task-Based Problem Solving Adapters (TPSAs) for modeling a humam solution (through activity-centered analysis) to a software solution (in form of computer-based artifact). TPSAs are derived from the problem solving pattern or consistent problem solving structures/strategies employed by practitioners while designing solutions to complex problems. The adapters developed by us lead toward human-centeredness in their design and underpinning that help us to address the pragmatic task constraints through a range of technologies like neural networks, fuzzy logic, and genetic algorithms. We also outline an example of applying the TPSAs to develop a working system for assisting sales engineers of an electrical manufacturing firm in preparing indent and monitoring the status of orders in the company.

Modeling of Task Ontology for Small Unit Operation : the Case of NGOs (특정주제 정보관리를 위한 온톨로지 모형 연구)

  • Yoo, Sa-Rah
    • Journal of the Korean Society for information Management
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    • v.24 no.1 s.63
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    • pp.31-53
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    • 2007
  • This paper presents a model of Task-Ontology for small unit operations(SUO) such as nongovernment organizations Despite the rapid development and extension of NGO in domestic area, most have insufficient structural domain resources in existence and underestimate the importance of information management. To improve the citizen's participation and to activate the conjoint actions among the NGO, which are critical to its social role-playing in global society, the modeling Task-Ontology is ultimately intended to implement the knowledge management system of NGO. In the perspective of ontology competency, not only the analysis of resources in vary, but also in-depth Interviews with the NGO practicing personnels and subject experts, and also the intensive observations of task-processing are required for the knowledge acquisition.

Development of Accident Classification Model and Ontology for Effective Industrial Accident Analysis based on Textmining (효과적인 산업재해 분석을 위한 텍스트마이닝 기반의 사고 분류 모형과 온톨로지 개발)

  • Ahn, Gilseung;Seo, Minji;Hur, Sun
    • Journal of the Korean Society of Safety
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    • v.32 no.5
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    • pp.179-185
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    • 2017
  • Accident analysis is an essential process to make basic data for accident prevention. Most researches depend on survey data and accident statistics to analyze accidents, but these kinds of data are not sufficient for systematic and detailed analysis. We, in this paper, propose an accident classification model that extracts task type, original cause materials, accident type, and the number of deaths from accident reports. The classification model is a support vector machine (SVM) with word occurrence features, and these features are selected based on mutual information. Experiment shows that the proposed model can extract task type, original cause materials, accident type, and the number of deaths with almost 100% accuracy. We also develop an accident ontology to express the information extracted by the classification model. Finally, we illustrate how the proposed classification model and ontology effectively works for the accident analysis. The classification model and ontology are expected to effectively analyze various accidents.

A Web-Based Domain Ontology Construction Modelling and Application in the Wetland Domain

  • Xing, Jun;Han, Min
    • Journal of Korea Multimedia Society
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    • v.10 no.6
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    • pp.754-759
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    • 2007
  • Methodology of ontology building based on Web resources will not only reduce significantly the ontology construction period, but also enhance the quality of the ontology. Remarkable progress has been achieved in this regard, but they encounter similar difficulties, such as the Web data extraction and knowledge acquisition. This paper researches on the characteristics of ontology construction data, including dynamics, largeness, variation and openness and other features, and the fundamental issue of ontology construction - formalized representation method. Then, the key technologies used in and the difficulties with ontology construction are summarized. A software Model-OntoMaker (Ontology Maker) is designed. The model is innovative in two regards: (1) the improvement of generality: the meta learning machine will dynamically pick appropriate ontology learning methodologies for data of different domains, thus optimizing the results; (2) the merged processing of (semi-) structural and non-structural data. In addition, as known to all wetland researchers, information sharing is vital to wetland exploitation and protection, while wetland ontology construction is the basic task for information sharing. OntoMaker constructs the wetland ontologies, and the model in this work can also be referred to other environmental domains.

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A Study on Location-Based Services Based on Semantic Web

  • Kim, Jong-Woo;Kim, Ju-Yeon;Kim, Chang-Soo
    • Journal of Korea Multimedia Society
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    • v.10 no.12
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    • pp.1752-1761
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    • 2007
  • Location-based services are a recent concept that integrates a mobile device's location with other information in order to provide added value to a user. Although Location-based Services provide users with comfortable information, it is a complex task to manage and share heterogeneous and numerous data in decentralized environments. In this paper, we propose the Semantic LBS Model as one of the solution to resolve the problem. The Semantic LBS Model is a LBS middleware model that includes an ontology-based data model for LBS POI information and its processing mechanism based on Semantic Web technologies. Our model enables POI information to be described and retrieved over various domain-specific ontologies based on our proposed POIDL ontology. This mechanism provide rich expressiveness, interoperability, flexibility in describing and using information about POls, and it can enhance POI retrieval services.

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Ontology-Based Multi-level Knowledge Framework for a Knowledge Management System for Discrete-Product Development

  • Lee, Jae-Hyun;Suh, Hyo-Won
    • International Journal of CAD/CAM
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    • v.5 no.1
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    • pp.99-109
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    • 2005
  • This paper introduces an approach to an ontology-based multi-level knowledge framework for a knowledge management system for discrete-product development. Participants in a product life cycle want to share comprehensive product knowledge without any ambiguity and heterogeneity. However, previous knowledge management approaches are limited in providing those aspects: therefore, we suggest an ontology-based multi-level knowledge framework (OBMKF). The bottom level, the axiom, specifies the semantics of concepts and relations of knowledge so ambiguity can be alleviated. The middle level is a product development knowledge map; it defines the concepts and the relations of the product domain knowledge and guides the engineer to process their engineering decisions. The middle level is then classified further into more detailed levels, such as generic product level, specific product level, product version level, and manufactured item level, according to the various viewpoints. The top level is specialized knowledge for a specific domain that gives the solution of a specific task or problem. It is classified into three knowledge types: expert knowledge, engineering function knowledge, and data-analysis-based knowledge. This proposed framework is based on ontology to accommodate a comprehensive range of knowledge and is represented with first-order logic to maintain a uniform representation.