Relevant bibliographies by topics / Distributed ontology

Academic literature on the topic 'Distributed ontology'

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Published: 14 March 2023

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Journal articles on the topic "Distributed ontology"

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Liu, Kun, Liang Zhang, Sheng Qun Tang, and Xue Qin. "A Revised Distributed Interpretation for Ontology Integration." Advanced Materials Research 756-759 (September 2013): 3440–45. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.3440.

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Under the background of information integration, the semantics of ontology integration is still an open issue. In this paper, we propose a revised distributed interpretation which is adapted from distributed description logics. In our proposal, ontology integration is taken as global ontology and local ontologies connected by ontology mapping. They are respectively interpreted with DL semantics and Semantic Import semantics. In this way, our method can facilitate understanding and maintenance of ontology integration.
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Zhang, Ming E., and Hui Zhang. "Applied-Information Technology in Design of Ontology Integration of Clinical Medicine and Diagnosis System Based on Knowledge Management." Advanced Materials Research 978 (June 2014): 197–200. http://dx.doi.org/10.4028/www.scientific.net/amr.978.197.

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Study on the clinical medical knowledge engineering, aims to build a large-scale, shared, reusable medical knowledge base, so as to provide the intelligent expert system of medicine, medical information retrieval system, medical education, medical natural language understanding etc.. In this paper, based on ontology integration technology, proposes an ontology integration of clinical medical knowledge management and computer-aided diagnosis system framework based on distributed ontology integration, and the technologies related to the knowledge management system is researched deeply, proposes a distributed ontology integration method based on semantics, in order to solve the information can not be shared between distributed information the distribution system and the problem of ontology integration, build a semantic platform can share the definition, design distributed ontology integration adapter, a reduction algorithm was proposed for distributed ontology integration relation, the ontology integration, reduce the redundant relation integrated ontology language, improving the quality and efficiency of ontology integration.
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Ras, Z. "Ontology-based distributed autonomous knowledge systems." Information Systems 29, no. 1 (March 2004): 47–58. http://dx.doi.org/10.1016/s0306-4379(03)00033-4.

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Randall, Dave, Rob Procter, Yuwei Lin, Meik Poschen, Wes Sharrock, and Robert Stevens. "Distributed ontology building as practical work." International Journal of Human-Computer Studies 69, no. 4 (April 2011): 220–33. http://dx.doi.org/10.1016/j.ijhcs.2010.12.011.

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CHEN, YUH-JEN, YUH-MIN CHEN, YUNG-SHENG SU, and CHIUN-CHENG WEN. "ONTOLOGY-BASED DISTRIBUTED CASE-BASED REASONING IN VIRTUAL ENTERPRISES." International Journal of Software Engineering and Knowledge Engineering 19, no. 08 (December 2009): 1039–82. http://dx.doi.org/10.1142/s0218194009004544.

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Given the advent of knowledge-based economies and virtual-enterprise business models, enterprises get the knowledge not only from themselves but also from others. Distributed case-based reasoning systems (DCBRS) play important roles in knowledge-driven virtual enterprises by supporting knowledge sharing. This study develops a novel mechanism for ontology-based distributed case-based reasoning using ontology and a proposed multistage algorithm to effectively support knowledge sharing within a virtual enterprise environment. Tasks involved in this study are as follows: (i) design an ontology-based distributed case-based reasoning architecture and procedure, (ii) develop techniques related to the ontology-based distributed case-based reasoning, and (iii) implement an ontology-based distributed case-based reasoning mechanism. Developing methods associated with ontology-based distributed case-based reasoning involves the definition and representation of a user query model, definition and representation of a knowledge case model, definition and establishment of knowledge case index structure, and development of a distributed knowledge case retrieval and knowledge case adaptation methods. Study results will facilitate heterogeneous knowledge sharing among enterprises participating in a virtual enterprise.
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Saba, Farzaneh, and Yasser Mohamed. "An ontology-driven framework for enhancing reusability of distributed simulation modeling of industrial construction processes." Canadian Journal of Civil Engineering 40, no. 9 (September 2013): 917–26. http://dx.doi.org/10.1139/cjce-2011-0489.

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This paper describes an ontology-driven framework for developing distributed simulation modeling of construction processes. The research described in the paper is motivated by the necessity of knowledge sharing between distributed simulation modeling collaborators, and reuse and portability challenges in construction simulation models. Our approach addresses these challenges through ontological modeling and linking of construction simulation modeling components including (i) ontology of construction process, (ii) ontology of simulation world view, and (iii) ontology of distributed simulation modeling application tool. Within the paper, ontology driven approach and mapping of ontologies for information transference between simulation components has been described. Another discussed application of ontologies is structuring of simulation modeling development through use of reusable elements. A large-scale distributed simulation model of industrial construction processes has been outlined to illustrate the application of the approach.
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Lazarre, Warda, Kaladzavi Guidedi, Samdalle Amaria, and Kolyang. "Modular Ontology Design: A State-of-Art of Diseases Ontology Modeling and Possible Issue." Revue d'Intelligence Artificielle 36, no. 3 (June 30, 2022): 497–501. http://dx.doi.org/10.18280/ria.360319.

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The evolution of ontological engineering leaded authors to use some techniques of software engineering to design ontologies. Are obtained from these techniques the monolithic or modularized Ontologies. When is difficult to reuse some concepts of monolithic ontologies, modularized Ontologies facilitate ontology management, understandability and reuse. This paper aims to survey on ontology modularization techniques and their contribution in biomedical ontologies design. Modularization reposed on appropriated techniques and some challenges related to ontology reused, scalable querying, collaborative authoring, and distributed reasoning. For most of disease ontologies, more especially ontologies which reused IDO, these challenges are not considered, and most of them are implemented with OWL language and the novel mode to construct ontology’s purpose is to facilitate reuse and interoperability of ontologies ensured by modularization.
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Yang, Soo Mi. "Efficient Ontology Integration Model for Better Inference in Context Aware Computing." Advanced Materials Research 268-270 (July 2011): 841–46. http://dx.doi.org/10.4028/www.scientific.net/amr.268-270.841.

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In this paper, we describe efficient ontology integration model for better context inference based on distributed ontology framework. Context aware computing with inference based on ontology is widely used in distributed surveillance environment. In such a distributed surveillance environment, surveillance devices such as smart cameras may carry heterogeneous video data with different transmission ranges, latency, and formats. However even smart devices, they generally have small memory and power which can manage only part of ontology data. In our efficient ontology integration model, each of agents built in such devices get services not only from a region server, but also peer servers. For such a collaborative network, an effective cache framework that can handle heterogeneous devices is required for the efficient ontology integration. In this paper, we propose a efficient ontology integration model which is adaptive to the actual device demands and that of its neighbors. Our scheme shows the efficiency of model resulted in better context inference.
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Adel, Ebtsam, Shaker El-Sappagh, Sherif Barakat, Jong-Wan Hu, and Mohammed Elmogy. "An Extended Semantic Interoperability Model for Distributed Electronic Health Record Based on Fuzzy Ontology Semantics." Electronics 10, no. 14 (July 19, 2021): 1733. http://dx.doi.org/10.3390/electronics10141733.

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Semantic interoperability of distributed electronic health record (EHR) systems is a crucial problem for querying EHR and machine learning projects. The main contribution of this paper is to propose and implement a fuzzy ontology-based semantic interoperability framework for distributed EHR systems. First, a separate standard ontology is created for each input source. Second, a unified ontology is created that merges the previously created ontologies. However, this crisp ontology is not able to answer vague or uncertain queries. We thirdly extend the integrated crisp ontology into a fuzzy ontology by using a standard methodology and fuzzy logic to handle this limitation. The used dataset includes identified data of 100 patients. The resulting fuzzy ontology includes 27 class, 58 properties, 43 fuzzy data types, 451 instances, 8376 axioms, 5232 logical axioms, 1216 declarative axioms, 113 annotation axioms, and 3204 data property assertions. The resulting ontology is tested using real data from the MIMIC-III intensive care unit dataset and real archetypes from openEHR. This fuzzy ontology-based system helps physicians accurately query any required data about patients from distributed locations using near-natural language queries. Domain specialists validated the accuracy and correctness of the obtained results.
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Choukri, Djellali. "A New Distributed Expert System to Ontology Evaluation." Procedia Computer Science 37 (2014): 48–55. http://dx.doi.org/10.1016/j.procs.2014.08.011.

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Dissertations / Theses on the topic "Distributed ontology"

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Mutharaju, Raghava. "Distributed Rule-Based Ontology Reasoning." Wright State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=wright1472534764.

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Weng, Zumao. "Distributed knowledge based image contents retrieval and exploration." Thesis, University of Ulster, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.370088.

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Mena, Eduardo Illarramendi Arantza. "Ontology-based query processing for global information systems /." Boston [u.a.] : Kluwer Acad. Publ, 2001. http://www.loc.gov/catdir/enhancements/fy0813/2001029621-d.html.

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Tenschert, Axel [Verfasser], and Michael [Akademischer Betreuer] Resch. "Ontology matching in a distributed environment / Axel Tenschert ; Betreuer: Michael Resch." Stuttgart : Universitätsbibliothek der Universität Stuttgart, 2016. http://d-nb.info/1130148556/34.

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Gu, Xuan. "Selective Data Replication for Distributed Geographical Data Sets." Thesis, University of Canterbury. Computer Science and Software Engineering, 2008. http://hdl.handle.net/10092/2545.

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The main purpose of this research is to incorporate additional higher-level semantics into the existing data replication strategies in such a way that their flexibility and performance can be improved in favour of both data providers and consumers. The resulting approach from this research is referred to as the selective data replication system. With this system, the data that has been updated by a data provider is captured and batched into messages known as update notifications. Once update notifications are received by data consumers, they are used to evaluate so-called update policies, which are specified by data consumers containing details on when data replications need to occur and what data needs to be updated during the replications.
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Halilaj, Lavdim [Verfasser]. "An Approach for Collaborative Ontology Development in Distributed and Heterogeneous Environments / Lavdim Halilaj." Bonn : Universitäts- und Landesbibliothek Bonn, 2019. http://d-nb.info/117773480X/34.

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Kim, Taekyu. "Ontology/Data Engineering Based Distributed Simulation Over Service Oriented Architecture For Network Behavior Analysis." Diss., The University of Arizona, 2008. http://hdl.handle.net/10150/193678.

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As network uses increase rapidly and high quality-of-service (QoS) is required, efficient network managing methods become important. Many previous studies and commercial tools of network management systems such as tcpdump, Ethereal, and other applications have weaknesses: limited size of files, command line execution, and large memory and huge computational power requirement. Researchers struggle to find fast and effective analyzing methods to save maintenance budgets and recover from systematic problems caused by the rapid increment of network traffic or intrusions. The main objective of this study is to propose an approach to deal with a large amount of network behaviors being quickly and efficiently analyzed. We study an ontology/data engineering methodology based network analysis system. We design a behavior, which represents network traffic activity and network packet information such as IP addresses, protocols, and packet length, based on the System Entity Structure (SES) methodology. A significant characteristic of SES, a hierarchical tree structure, enables systems to access network packet information quickly and efficiently. Also, presenting an automated system design is the secondary purpose of this study. Our approach shows adaptive awareness of pragmatic frames (contexts) and makes a network traffic analysis system with high throughput and a fast response time that is ready to respond to user applications. We build models and run simulations to evaluate specific purposes, i.e., analyzing network protocols use, evaluating network throughput, and examining intrusion detection algorithms, based on Discrete Event System Specification (DEVS) formalism. To study speed up, we apply a web-based distributed simulation methodology. DEVS/Service Oriented Architecture (DEVS/SOA) facilitates deploying workloads into multi-servers and consequently increasing overall system performance. In addition to the scalability limitations, both tcpdump and Ethereal have a security issue. As well as basic network traffic information, captured files by these tools contain secure information: user identification numbers and passwords. Therefore, captured files should not allow to be leaked out. However, network analyses need to be performed outside target networks in some cases. The distributed simulation--allocating distributing models inside networks and assigning analyzing models outside networks--also allows analysis of network behaviors out of networks while keeping important information secured.
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Wariyapola, Pubudu C. (Pubudu Chaminda) 1972. "Towards an ontology and metadata structure for a distributed information system for coastal zone management." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/80236.

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Milliner, Stephen William. "Dynamic resolution of conceptual heterogenity in large scale distributed information systems." Thesis, Queensland University of Technology, 2001.

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Ducrou, Amanda Joanne. "Complete interoperability in healthcare technical, semantic and process interoperability through ontology mapping and distributed enterprise integration techniques /." Access electronically, 2009. http://ro.uow.edu.au/theses/3048.

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Books on the topic "Distributed ontology"

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Kashif, Khan Falahudin. A distributed ontology architecture for highway construction: Toward semantic exchange of infrastructure knowledge. Ottawa: National Library of Canada, 2003.

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Mena, Eduardo. Ontology-Based Query Processing for Global Information Systems. Boston, MA: Springer US, 2001.

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Arantza, Illarramendi, ed. Ontology-based query processing for global information systems. Boston: Kluwer Academic Publishers, 2001.

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Orozco, J. Martín Serrano. Applied Ontology Engineering in Cloud Services, Networks and Management Systems. Boston, MA: Springer US, 2012.

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Explorer's guide to the Semantic Web. Greenwich: Manning, 2004.

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Haase, Peter. Semantic technologies for distributed information systems. Karlsruhe: Univ.-Verl. Karlsruhe, 2006.

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R, Meersman, International Symposium on Distributed Objects and Applications (2002 : Catania, Italy), and International Conference on Ontologies Databases and Applications of Semantics (2002 : Catania, Italy), eds. On the move to meaningful Internet systems 2003: CoopIS, DOA, and ODBASE : OTM confederated international conferences CoopIS, DOA, and ODBASE 2003, Catania, Sicily, Italy, November 3-7, 2003 : proceedings. New York: Springer-Verlag, 2003.

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R, Meersman, Tari Zahir, and HCI-SWWA (2003 : Catania, Sicily), eds. On the move to meaningful Internet systems 2003: OTM 2003 workshops : OTM confederated international workshops : HCI-SWWA, IPW, JTRES, WORM, WMS, and WSRM 2003, Catania, Sicily, November 3-7, 2003 : proceedings. New York: Springer-Verlag, 2003.

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Automated Agent Ontology Creation for Distributed Databases. Storming Media, 2004.

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Mena, Eduardo, and Arantza Illarramendi. Ontology-Based Query Processing for Global Information Systems (The International Series in Engineering and Computer Science). Springer, 2001.

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Book chapters on the topic "Distributed ontology"

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Bermejo, A. J., J. Villadangos, J. J. Astrain, and A. Córdoba. "Ontology Based Road Traffic Management." In Intelligent Distributed Computing VI, 103–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-32524-3_14.

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McGuinness, Deborah L. "Conceptual Modeling for Distributed Ontology Environments." In Lecture Notes in Computer Science, 100–112. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/10722280_7.

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Alamri, Abdullah, and Peter Bertok. "Distributed Store for Ontology Data Management." In Computer and Information Science 2012, 15–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30454-5_2.

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Schlicht, Anne, and Heiner Stuckenschmidt. "Distributed Resolution for Expressive Ontology Networks." In Web Reasoning and Rule Systems, 87–101. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-05082-4_7.

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Al-Fedaghi, Sabah. "Toward Flow-Based Ontology." In Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, 125–37. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33810-1_10.

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Böhler, Dominik. "Ontology-based Distributed Organizing: Answering the Challenges of Distributed Organizing." In On the Nature of Distributed Organizing, 117–25. Wiesbaden: Springer Fachmedien Wiesbaden, 2014. http://dx.doi.org/10.1007/978-3-658-06123-4_12.

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Rodríguez-García, Miguel Ángel, Luis Omar Colombo-Mendoza, Rafael Valencia-García, Antonio A. Lopez-Lorca, and Ghassan Beydoun. "Ontology-Based Music Recommender System." In Distributed Computing and Artificial Intelligence, 12th International Conference, 39–46. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19638-1_5.

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Dhingra, Vandana, and Komal Kumar Bhatia. "SemCrawl: Framework for Crawling Ontology Annotated Web Documents for Intelligent Information Retrieval." In Intelligent Distributed Computing, 213–23. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-11227-5_19.

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Sriharee, Natenapa, and Twittie Senivongse. "Discovering Web Services Using Behavioural Constraints and Ontology." In Distributed Applications and Interoperable Systems, 248–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-40010-3_22.

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Subhashree, S., Rajeev Irny, and P. Sreenivasa Kumar. "Review of Approaches for Linked Data Ontology Enrichment." In Distributed Computing and Internet Technology, 27–49. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-72344-0_2.

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Conference papers on the topic "Distributed ontology"

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de Souza Pereira, Joao Henrique, Sergio Takeo Kofuji, and Pedro Frosi Rosa. "Distributed Systems Ontology." In 2009 3rd International Conference on New Technologies, Mobility and Security (NTMS). IEEE, 2009. http://dx.doi.org/10.1109/ntms.2009.5384822.

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Campos, R., O. Rojas, M. Marin, and M. Mendoza. "Distributed Ontology-Driven Focused Crawling." In 2013 21st Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP 2013). IEEE, 2013. http://dx.doi.org/10.1109/pdp.2013.23.

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Khafagy, Mohamed Helmy, and Haytham Tawfeek Al Feel. "Distributed Ontology Cloud Storage System." In 2012 Second Symposium on Network Cloud Computing and Applications (NCCA). IEEE, 2012. http://dx.doi.org/10.1109/ncca.2012.13.

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Wouters, Laurent, and Marie-Pierre Gervais. "Ontology Transformations." In 2012 16th IEEE International Enterprise Distributed Object Computing Conference (EDOC 2012). IEEE, 2012. http://dx.doi.org/10.1109/edoc.2012.18.

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Sarkar, Arkopaul, and Dusan Sormaz. "Foundation Ontology for Distributed Manufacturing Process Planning." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-60159.

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Distributed computer integrated manufacturing is increasingly adopting cloud computing, software-as-a-service (SaaS) and multi-agent systems as steps towards “design anywhere, build anywhere” strategy. In this scenario, foundation ontologies not only serve as common message exchange structure among distributed agents but also provide reasoning service to extract implicit knowledge from explicit information already stored in the knowledge base. Foundation ontologies, comprised of most general concepts of a domain, provide a common semantic structure to the domain-level ontologies, which capture details of multi-disciplinary manufacturing knowledge. In this paper, foundation ontology for manufacturing process planning is proposed and manufacturing process selection information of a sample prismatic design feature is modeled using the proposed foundation ontology, as a case study.
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Juffinger, Andreas, Thomas Neidhart, Albert Weichselbraun, Gerhard Wohlgenannt, Michael Granitzer, Roman Kern, and Arno Scharl. "Distributed Web2.0 crawling for ontology evolution." In 2007 2nd International Conference on Digital Information Management. IEEE, 2007. http://dx.doi.org/10.1109/icdim.2007.4444293.

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Abdoli, F., and M. Kahani. "Ontology-based distributed intrusion detection system." In 2009 14th International CSI Computer Conference (CSICC 2009) (Postponed from July 2009). IEEE, 2009. http://dx.doi.org/10.1109/csicc.2009.5349372.

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Liang, Ye, Hong Bao, and Hongzhe Liu. "Hybrid Ontology Integration for Distributed System." In Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007). IEEE, 2007. http://dx.doi.org/10.1109/snpd.2007.305.

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Qiu, Xiuqin, and Jun Yue. "Ontology based distributed agricultural knowledge management." In 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery (FSKD). IEEE, 2010. http://dx.doi.org/10.1109/fskd.2010.5569262.

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Souza, E. F., R. A. Falbo, and N. L. Vijaykumar. "Using Ontology Patterns for Building a Reference Software Testing Ontology." In 2013 17th IEEE International Enterprise Distributed Object Computing Conference Workshops (EDOCW). IEEE, 2013. http://dx.doi.org/10.1109/edocw.2013.10.

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Reports on the topic "Distributed ontology"

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Ceruti, Marion G., and Dwight R. Wilcox. Sensor Ontology Integration for the Knowledge Management for Distributed-Tracking (KMDT) Program. Fort Belvoir, VA: Defense Technical Information Center, June 2006. http://dx.doi.org/10.21236/ada463094.

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