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Journal articles on the topic 'Graphics Ontology'

Author: Grafiati

Published: 4 June 2021

Last updated: 15 February 2022

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1

Li, Yue Li, and Ai Hua Ren. "Research on Ontology Structure Characteristics Analysis and Matching Application." Applied Mechanics and Materials 556-562 (May 2014): 4396–99. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.4396.

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According to the similarity between ontology and complex network, the article analyzes the network characteristics of ontology and brings forward a series of theories based on structural and semantic characteristics as well as quantization criteria for nodes and edges. These theories and quantization criteria are applied to the selection of core nodes and measurement of edge weight. In this article, the problem of ontology matching is transformed into the matching of weighed label graphics, which are based on individual characteristics and organizational structure. The matching of approximatel

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Xu, Cijun, Aiping Li, and Xuemei Liu. "Ontology-Based Knowledge Fusion Framework." Journal of Computer-Aided Design & Computer Graphics 22, no. 7 (2010): 1230–36. http://dx.doi.org/10.3724/sp.j.1089.2010.10897.

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3

Marick, Brian. "Methodology work is ontology work." ACM SIGPLAN Notices 39, no. 12 (2004): 64–72. http://dx.doi.org/10.1145/1052883.1052892.

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Colantonio, S., M. Martinelli, O. Salvetti, I. B. Gurevich, and Y. O. Trusova. "Cell image analysis ontology." Pattern Recognition and Image Analysis 18, no. 2 (2008): 332–41. http://dx.doi.org/10.1134/s1054661808020211.

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5

Vizcaíno, A., F. García, I. Caballero, J. C. Villar, and M. Piattini. "Towards an ontology for global software development." IET Software 6, no. 3 (2012): 214. http://dx.doi.org/10.1049/iet-sen.2011.0087.

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Hallberg, Niklas, Erland Jungert, and Sofie Pilemalm. "Ontology for Systems Development." International Journal of Software Engineering and Knowledge Engineering 24, no. 03 (2014): 329–45. http://dx.doi.org/10.1142/s0218194014500132.

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Software-intensive information systems have a major impact on our lives, both privately and professionally. Development of these systems is a complex activity that requires the involvement of people with different competences and skills. Even though software-intensive systems have been developed since the 1960s, the success rate is still low. A major hindrance to successful system development projects is the lack of consistent terminology. Since systems development is a collaborative activity, involving not only systems developers but also domain experts and user representatives, the understan

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Chen, Tong, Beibei Fan, Dongping Chen, and Cong Li. "A Knowledge Modeling Method for Computer Graphics Design & Production Based on Ontology." MATEC Web of Conferences 100 (2017): 02041. http://dx.doi.org/10.1051/matecconf/201710002041.

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Koukovini, Maria N., Eugenia I. Papagiannakopoulou, Georgios V. Lioudakis, Nikolaos Dellas, Dimitra I. Kaklamani, and Iakovos S. Venieris. "An ontology‐based approach towards comprehensive workflow modelling." IET Software 8, no. 2 (2014): 73–85. http://dx.doi.org/10.1049/iet-sen.2013.0037.

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Zeshan, Furkh, Radziah Mohamad, Mohammad Nazir Ahmad, et al. "Ontology‐based service discovery framework for dynamic environments." IET Software 11, no. 2 (2017): 64–74. http://dx.doi.org/10.1049/iet-sen.2016.0048.

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Kim, Kyoung-Yun. "Ontology and Assembly Joint Topology Representation." Computer-Aided Design and Applications 5, no. 5 (2008): 630–38. http://dx.doi.org/10.3722/cadaps.2008.630-638.

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Buranarach, Marut, Thepchai Supnithi, Ye Myat Thein, et al. "OAM: An Ontology Application Management Framework for Simplifying Ontology-Based Semantic Web Application Development." International Journal of Software Engineering and Knowledge Engineering 26, no. 01 (2016): 115–45. http://dx.doi.org/10.1142/s0218194016500066.

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Although the Semantic Web data standards are established, ontology-based applications built on the standards are relatively limited. This is partly due to high learning curve and efforts demanded in building ontology-based Semantic Web applications. In this paper, we describe an ontology application management (OAM) framework that aims to simplify creation and adoption of ontology-based application that is based on the Semantic Web technology. OAM introduces an intermediate layer between user application and programming and development environment in order to support ontology-based data publis

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LAM, TOBY H. W., JAMES N. K. LIU, and RAYMOND S. T. LEE. "MASTER: AN INTELLIGENT ONTOLOGY-BASED MULTI-AGENT SYSTEM FOR SIGHTSEER." International Journal of Software Engineering and Knowledge Engineering 19, no. 02 (2009): 137–57. http://dx.doi.org/10.1142/s021819400900412x.

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Recently, semantic web has received substantial attention from the research community. Semantic web aims to provide a new framework that can enable knowledge sharing and reusing. Semantic web is a collection of web technologies that include a number of markup languages such as RDF, OWL and RDFS. These markup languages are used for modeling a domain ontology. By using ontology to model resources, humans and computers (software agents) can have a consensus on the resource structure. The use of these technologies allows the creation of a more effective web search system. In this paper, we modeled

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Raubal, Martin, and Werner Kuhn. "Ontology-Based Task Simulation." Spatial Cognition & Computation 4, no. 1 (2004): 15–37. http://dx.doi.org/10.1207/s15427633scc0401_3.

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Lee, Jaehyun, Hyowon Suh, and Soon Hung Han. "Ontology-based Knowledge Framework for Product Development." Computer-Aided Design and Applications 2, no. 5 (2005): 635–43. http://dx.doi.org/10.1080/16864360.2005.10738328.

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Nanda, Jyotirmaya, Timothy W. Simpson, Soundar R. T. Kumara, and Steven B. Shooter. "A Methodology for Product Family Ontology Development Using Formal Concept Analysis and Web Ontology Language." Journal of Computing and Information Science in Engineering 6, no. 2 (2005): 103–13. http://dx.doi.org/10.1115/1.2190237.

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The use of ontologies for information sharing is well documented in the literature, but the lack of a comprehensive and systematic methodology for constructing product ontologies has limited the process of developing ontologies for design artifacts. In this paper we introduce the Product Family Ontology Development Methodology (PFODM), a novel methodology to develop formal product ontologies using the Semantic Web paradigm. Within PFODM, Formal Concept Analysis (FCA) is used first to identify similarities among a finite set of design artifacts based on their properties and then to develop and

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García-Rojas, A., F. Vexo, D. Thalmann, et al. "Emotional face expression profiles supported by virtual human ontology." Computer Animation and Virtual Worlds 17, no. 3-4 (2006): 259–69. http://dx.doi.org/10.1002/cav.130.

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ZHANG, JIANFU, PINGFA FENG, ZHIJUN WU, DINGWEN YU, and KEN CHEN. "ACTIVITY BASED CIM MODELING AND TRANSFORMATION FOR BUSINESS PROCESS SYSTEMS." International Journal of Software Engineering and Knowledge Engineering 20, no. 03 (2010): 289–309. http://dx.doi.org/10.1142/s0218194010004736.

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Computation-Independent Model (CIM) to capture domain requirements and the transformation from CIM to the Platform-Independent Model (PIM) are two crucial parts of the Model-Driven Architecture (MDA). This paper presents an ontology-activity-based CIM modeling approach to achieve a semi-automatic transformation from CIM to PIM. It proposes that the key elements in business process modeling are activities and these should therefore form the basis in constructing the domain ontology. Aiming to provide the key description capability for the process model, it discusses the hierarchy of the model b

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CHAN, CHRISTINE W. "FROM KNOWLEDGE MODELING TO ONTOLOGY CONSTRUCTION." International Journal of Software Engineering and Knowledge Engineering 14, no. 06 (2004): 603–24. http://dx.doi.org/10.1142/s0218194004001816.

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This paper presents the Knowledge Modeling System (KMS) and its application. The KMS supports users in formalizing and documenting knowledge elements acquired for development of knowledge-based systems. The system was developed based on a knowledge modeling technique called the Inferential Modeling Technique. It facilitates building an application ontology of a domain by explicitly structuring and formalizing both domain and task knowledge of any industrial problem domain. The system also supports knowledge sharing by converting the ontology into the Extensible Mark-Up Language (XML). The tool

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RUIZ, FRANCISCO, AURORA VIZCAÍNO, MARIO PIATTINI, and FELIX GARCÍA. "AN ONTOLOGY FOR THE MANAGEMENT OF SOFTWARE MAINTENANCE PROJECTS." International Journal of Software Engineering and Knowledge Engineering 14, no. 03 (2004): 323–49. http://dx.doi.org/10.1142/s0218194004001646.

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Different proposals exist to represent the software maintenance process. However most of them are very informal or too focussed on a specific goal. We have developed a semi-formal ontology where the main concepts, according to the literature related to software maintenance, have been described. This ontology, besides representing static aspects, also represents dynamic issues related to the management of software maintenance projects. In order to develop an ontology a suitable methodology should also be followed. REFSENO was the methodology used in this work. The ontology that this work presen

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Zagoruiko, N. G., S. E. Gulyaevskii, and B. Ya Kovalerchuk. "Ontology of the data mining subject domain." Pattern Recognition and Image Analysis 17, no. 3 (2007): 349–56. http://dx.doi.org/10.1134/s1054661807030017.

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LIU, Kai-Peng, and Bin-Xing FANG. "Ontology Induction Based on Social Annotations." Chinese Journal of Computers 33, no. 10 (2010): 1823–34. http://dx.doi.org/10.3724/sp.j.1016.2010.01823.

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Ameri, Farhad, and Joshua D. Summers. "An Ontology for Representation of Fixture Design Knowledge." Computer-Aided Design and Applications 5, no. 5 (2008): 601–11. http://dx.doi.org/10.3722/cadaps.2008.601-611.

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Kim, Kyoung-Yun, Hyungjeong Yang, and David G. Manley. "Assembly Design Ontology for Service-Oriented Design Collaboration." Computer-Aided Design and Applications 3, no. 5 (2006): 603–13. http://dx.doi.org/10.1080/16864360.2006.10738414.

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24

JING, YIXIN, DONGWON JEONG, and DOO-KWON BAIK. "AN INFERENCE-ENABLED ACCESS CONTROL MODEL FOR RDF ONTOLOGY." International Journal of Software Engineering and Knowledge Engineering 19, no. 03 (2009): 339–60. http://dx.doi.org/10.1142/s0218194009004209.

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Although RDF ontologies are expressed based on XML syntax, existing methods to protect XML documents are not suitable for securing RDF ontologies. The graph style and inference feature of RDF ontologies demands new methods for access control. Driven by this goal, this paper proposes a query-oriented model for RDF ontology access control. The model adopts the concept of ontology view to rewrite user queries. In our approach, ontology views define accessible ontology concepts and instances a user can visit, and enables a controlled inference capability for the user. The design of the views guara

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25

Weichbroth, Paweł. "Fluent Editor and Controlled Natural Language in Ontology Development." International Journal on Artificial Intelligence Tools 28, no. 04 (2019): 1940007. http://dx.doi.org/10.1142/s0218213019400074.

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Ontologies facilitate concise communication across applications and people, by means of precisely defined terms that provide a shared and common understanding. However, typically, the development of an ontology entails the commitment of multiple users and requires significant skills and knowledge in this area. To face this problem, in this paper we discuss the features and capabilities of Fluent Editor and, based on a real-life example, present the properties of Controlled Natural Language (CNL). Firstly, the editor is designed to be user-friendly and is customized with a ribbon and self-exten

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Gurevich, I. B., O. Salvetti, and Yu O. Trusova. "Fundamental concepts and elements of image analysis ontology." Pattern Recognition and Image Analysis 19, no. 4 (2009): 603–11. http://dx.doi.org/10.1134/s1054661809040051.

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ZHONG, Qian, Juan-Zi LI, Jie TANG, and Li-Zhu ZHOU. "Data Field Based Large Scale Ontology Mapping." Chinese Journal of Computers 33, no. 6 (2010): 955–65. http://dx.doi.org/10.3724/sp.j.1016.2010.00955.

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ZHONG, Xiu-Qin, Hong-Guang FU, Li SHE, and Bin HUANG. "Geometry Knowledge Acquisition and Representation on Ontology." Chinese Journal of Computers 33, no. 1 (2010): 167–74. http://dx.doi.org/10.3724/sp.j.1016.2010.00167.

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29

Tang, Wenhu, Long Yan, Zhen Yang, and Qinghua Henry Wu. "Improved document ranking in ontology‐based document search engine using evidential reasoning." IET Software 8, no. 1 (2014): 33–41. http://dx.doi.org/10.1049/iet-sen.2013.0015.

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30

Zand, Mohsen, Shyamala Doraisamy, Alfian Abdul Halin, and Mas Rina Mustaffa. "Ontology-Based Semantic Image Segmentation Using Mixture Models and Multiple CRFs." IEEE Transactions on Image Processing 25, no. 7 (2016): 3233–48. http://dx.doi.org/10.1109/tip.2016.2552401.

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31

Wendelberg, Linda. "An Ontological Framework to Facilitate Early Detection of ‘Radicalization’ (OFEDR)—A Three World Perspective." Journal of Imaging 7, no. 3 (2021): 60. http://dx.doi.org/10.3390/jimaging7030060.

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This paper presents an ontology that involves using information from various sources from different disciplines and combining it in order to predict whether a given person is in a radicalization process. The purpose of the ontology is to improve the early detection of radicalization in persons, thereby contributing to increasing the extent to which the unwanted escalation of radicalization processes can be prevented. The ontology combines findings related to existential anxiety that are related to political radicalization with well-known criminal profiles or radicalization findings. The softwa

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GAO, TONG, HUI MA, I.-LING YEN, LATIFUR KHAN, and FAROKH BASTANI. "A REPOSITORY FOR COMPONENT-BASED EMBEDDED SOFTWARE DEVELOPMENT." International Journal of Software Engineering and Knowledge Engineering 16, no. 04 (2006): 523–52. http://dx.doi.org/10.1142/s0218194006002872.

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The rapid growth in the demand for embedded systems and the increased complexity of embedded software pose an urgent need for advanced embedded software development techniques. Software technology is shifting toward semi-automated code generation and integration of systems from components. Component-based development (CBD) techniques can significantly reduce the time and cost for developing software systems. Furthermore, effective component retrieval is a fundamental issue in CBD. In this paper, we address the issues in designing software repositories for embedded software components. We devel

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33

Lindley, Joseph, Paul Coulton, and Rachel Cooper. "Why the Internet of Things needs Object Orientated Ontology." Design Journal 20, sup1 (2017): S2846—S2857. http://dx.doi.org/10.1080/14606925.2017.1352796.

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Khan, Md Tarique Hasan, Frédéric Demoly, and Kyoung-Yun Kim. "Formal ontology and CAD integration with macro parametric approach." Computer-Aided Design and Applications 14, sup1 (2017): 24–32. http://dx.doi.org/10.1080/16864360.2017.1308078.

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VASILAKIS, GEORGE, ALEJANDRA GARCIA-ROJAS, LAURA PAPALEO, et al. "KNOWLEDGE-BASED REPRESENTATION OF 3D MEDIA." International Journal of Software Engineering and Knowledge Engineering 20, no. 05 (2010): 739–60. http://dx.doi.org/10.1142/s0218194010004773.

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In recent years, 3D media have become more and more widespread and have been made available in numerous online repositories. A systematic and formal approach for representing and organizing shape-related information is needed to share 3D media, to communicate the knowledge associated to shape modeling processes and to facilitate its reuse in useful cross-domain usage scenarios. In this paper we present an initial attempt to formalize an ontology for digital shapes, called the Common Shape Ontology (CSO). We discuss about the rationale, the requirements and the scope of this ontology, we presen

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DURAK, UMUT, HALİT OǦUZTÜZÜN, and S. KEMAL İDER. "ONTOLOGY-BASED DOMAIN ENGINEERING FOR TRAJECTORY SIMULATION REUSE." International Journal of Software Engineering and Knowledge Engineering 19, no. 08 (2009): 1109–29. http://dx.doi.org/10.1142/s0218194009004532.

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We apply an ontology based knowledge and software reuse methodology adhering to domain engineering principles. Our domain is trajectory simulation. A trajectory simulation is a piece of software to calculate the flight path and other parameters of a munition, such as its orientation and angular rates, from launch to impact. Trajectory Simulation ONTology (TSONT) has been constructed as part of the domain analysis. Object oriented and function oriented reuse infrastructures have been built based upon TSONT following a model-driven development approach. Use of these infrastructures in simulation

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HE, HONGYUE, ZHIXUE WANG, QINGCHAO DONG, WEIZHONG ZHANG, and WEIXING ZHU. "ONTOLOGY-BASED SEMANTIC VERIFICATION FOR UML BEHAVIORAL MODELS." International Journal of Software Engineering and Knowledge Engineering 23, no. 02 (2013): 117–45. http://dx.doi.org/10.1142/s0218194013500010.

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UML is now popularly applied as a requirements modeling language for software system analysis and design, and the dynamic behaviors of system are described in UML behavioral model. As the UML model suffers from lack of well-defined formal semantics, it is difficult to formally analyze and verify the behavioral model. The paper presents a method of UML behavioral model verification based on Description Logic system and its formal inference. The semantics of UML behavioral models is divided into static semantics and dynamic semantics, which are formally specified in OWL DL ontology and DL-Safe r

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38

Witherell, Paul, Sundar Krishnamurty, and Ian R. Grosse. "Ontologies for Supporting Engineering Design Optimization." Journal of Computing and Information Science in Engineering 7, no. 2 (2006): 141–50. http://dx.doi.org/10.1115/1.2720882.

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This paper presents an optimization ontology and its implementation into a prototype computational knowledge-based tool dubbed ONTOP (ontology for optimization). Salient feature of ONTOP include a knowledge base that incorporates both standardized optimization terminology, formal method definitions, and often unrecorded optimization details, such as any idealizations and assumptions that may be made when creating an optimization model, as well as the model developer’s rationale and justification behind these idealizations and assumptions. ONTOP was developed using Protégé, a Java-based, free o

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Liang, Vei-Chung, and Christiaan J. J. Paredis. "A Port Ontology for Conceptual Design of Systems." Journal of Computing and Information Science in Engineering 4, no. 3 (2004): 206–17. http://dx.doi.org/10.1115/1.1778191.

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During conceptual design of systems, the emphasis is on generating the system architecture: the configuration of sub-systems and the interactions between them. Ports, as locations of intended interaction, play an important role at this stage of design. They are convenient abstractions for representing the intended exchange of signals, energy or material; they can be applied at different levels of detail, across different energy domains, and to all aspects of design: form, function, and behavior. But to play this versatile role, ports need to be represented in an unambiguous yet flexible fashio

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Elsayed, Eman, and Doaa Fathy. "Semantic Deep Learning to Translate Dynamic Sign Language." International Journal of Intelligent Engineering and Systems 14, no. 1 (2021): 316–25. http://dx.doi.org/10.22266/ijies2021.0228.30.

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Dynamic Sign Language Recognition aims to recognize hand gestures of any person. Dynamic Sign Language Recognition systems have challenges in recognizing the semantic of hand gestures. These challenges come from the personal differences in hand signs from one person to another. Real-life video gesture frames couldn’t be treated as frame-level as a static sign. This research proposes a semantic translation system for dynamic hand gestures using deep learning and ontology. We used the proposed MSLO (Multi Sign Language Ontology) in the semantic translation step. Also, any user can retrain the sy

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Camossi, Elena, Franca Giannini, and Marina Monti. "Deriving Functionality from 3D Shapes: Ontology Driven Annotation and Retrieval." Computer-Aided Design and Applications 4, no. 6 (2007): 773–82. http://dx.doi.org/10.1080/16864360.2007.10738510.

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42

Bao, Qiangwei. "Ontology-based Assembly Process Modeling with Element Extraction and Reasoning." Computer-Aided Design and Applications 19, no. 2 (2021): 280–92. http://dx.doi.org/10.14733/cadaps.2022.280-292.

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KWON, JUHUM, DONGWON JEONG, LEE-SUB LEE, and DOO-KWON BAIK. "INTELLIGENT SEMANTIC CONCEPT MAPPING FOR SEMANTIC QUERY REWRITING/OPTIMIZATION IN ONTOLOGY-BASED INFORMATION INTEGRATION SYSTEM." International Journal of Software Engineering and Knowledge Engineering 14, no. 05 (2004): 519–42. http://dx.doi.org/10.1142/s0218194004001762.

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Recently, ontology has been recognized as one of the most suitable global conceptual models for information integration architecture due to its easy taxonomical classification of data model and plentiful support of integrity constraint. However, the concept of mapping from global ontology to local information systems depends mostly on the simple metadata structures that allow for the mapping elements to be extracted with an If-Then-Else comparison statement. This kind of mapping is not suitable for ontology based data model in which the concepts are in the multiple subsumption relations. That

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Zhou, Jianhui, and Jihong Liu. "A Method of Automatically Extracting Domain Sub-ontology for Complex Product Knowledge Management." Journal of Computer-Aided Design & Computer Graphics 30, no. 6 (2018): 1118. http://dx.doi.org/10.3724/sp.j.1089.2018.16630.

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Umavathy, K., and P. Sankar. "Ontology based conceptual models for predicting fundamental organic reactivity." Journal of Molecular Graphics and Modelling 100 (November 2020): 107691. http://dx.doi.org/10.1016/j.jmgm.2020.107691.

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Ma, Jian, Runtong Zhang, Xiaomin Zhu, and Runqi Cao. "Process ontology technology in modeling clinical pathway information system." International Journal of Computers and Applications 42, no. 6 (2018): 550–57. http://dx.doi.org/10.1080/1206212x.2018.1478195.

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Cho, Joonmyun, Soonhung Han, and Hyun Kim. "Meta-ontology for automated information integration of parts libraries." Computer-Aided Design 38, no. 7 (2006): 713–25. http://dx.doi.org/10.1016/j.cad.2006.03.002.

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Gao, Wei. "Minimax Learning Rate for Multi-dividing Ontology Algorithm." Journal of Information and Computational Science 11, no. 6 (2014): 1853–60. http://dx.doi.org/10.12733/jics20103216.

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GARZÁS, JAVIER, and MARIO PIATTINI. "AN ONTOLOGY FOR UNDERSTANDING AND APPLYING OBJECT-ORIENTED DESIGN KNOWLEDGE." International Journal of Software Engineering and Knowledge Engineering 17, no. 03 (2007): 407–21. http://dx.doi.org/10.1142/s0218194007003318.

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After years of experience in object-oriented design, software engineers have accumulated a great deal of knowledge in the design and construction of object-oriented systems: important contributions to this field including principles, heuristics, lessons learned, bad smells, refactorings, and so on, with the resultant major improvements in software development. However, this large body of knowledge is still not well organized, its terminology is ambiguous, and it is very difficult to make practical use of the contributions made. In this regard, we believe it is important to define an ontology i

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Grenon, Pierre, and Barry Smith. "SNAP and SPAN: Towards Dynamic Spatial Ontology." Spatial Cognition & Computation 4, no. 1 (2004): 69–104. http://dx.doi.org/10.1207/s15427633scc0401_5.

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