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Qin, J.: Evolving paradigms of knowledge representation and organization : a comparative study of classification, XML/DTD and ontology (2003)
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- Abstract
- The different points of views an knowledge representation and organization from various research communities reflect underlying philosophies and paradigms in these communities. This paper reviews differences and relations in knowledge representation and organization and generalizes four paradigms-integrative and disintegrative pragmatism and integrative and disintegrative epistemologism. Examples such as classification, XML schemas, and ontologies are compared based an how they specify concepts, build data models, and encode knowledge organization structures. 1. Introduction Knowledge representation (KR) is a term that several research communities use to refer to somewhat different aspects of the same research area. The artificial intelligence (AI) community considers KR as simply "something to do with writing down, in some language or communications medium, descriptions or pictures that correspond in some salient way to the world or a state of the world" (Duce & Ringland, 1988, p. 3). It emphasizes the ways in which knowledge can be encoded in a computer program (Bench-Capon, 1990). For the library and information science (LIS) community, KR is literally the synonym of knowledge organization, i.e., KR is referred to as the process of organizing knowledge into classifications, thesauri, or subject heading lists. KR has another meaning in LIS: it "encompasses every type and method of indexing, abstracting, cataloguing, classification, records management, bibliography and the creation of textual or bibliographic databases for information retrieval" (Anderson, 1996, p. 336). Adding the social dimension to knowledge organization, Hjoerland (1997) states that knowledge is a part of human activities and tied to the division of labor in society, which should be the primary organization of knowledge. Knowledge organization in LIS is secondary or derived, because knowledge is organized in learned institutions and publications. These different points of views an KR suggest that an essential difference in the understanding of KR between both AI and LIS lies in the source of representationwhether KR targets human activities or derivatives (knowledge produced) from human activities. This difference also decides their difference in purpose-in AI KR is mainly computer-application oriented or pragmatic and the result of representation is used to support decisions an human activities, while in LIS KR is conceptually oriented or abstract and the result of representation is used for access to derivatives from human activities.
- Date
- 12. 9.2004 17:22:35
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Qin, J.; Paling, S.: Converting a controlled vocabulary into an ontology : the case of GEM (2001)
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- Date
- 24. 8.2005 19:20:22
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Qin, J.: ¬A relation typology in knowledge organization systems : case studies in the research data management domain (2018)
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- Source
- Challenges and opportunities for knowledge organization in the digital age: proceedings of the Fifteenth International ISKO Conference, 9-11 July 2018, Porto, Portugal / organized by: International Society for Knowledge Organization (ISKO), ISKO Spain and Portugal Chapter, University of Porto - Faculty of Arts and Humanities, Research Centre in Communication, Information and Digital Culture (CIC.digital) - Porto. Eds.: F. Ribeiro u. M.E. Cerveira
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Qin, J.; Lancaster, F.W.; Allen, B.: Types and levels of collaboration in interdisciplinary research in the sciences (1997)
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- Source
- Journal of the American Society for Information Science. 48(1997) no.10, S.893-916
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Chen, H.; Chung, W.; Qin, J.; Reid, E.; Sageman, M.; Weimann, G.: Uncovering the dark Web : a case study of Jihad on the Web (2008)
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- Source
- Journal of the American Society for Information Science and Technology. 59(2008) no.8, S.1347-1359
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Qin, J.; Creticos, P.; Hsiao, W.Y.: Adaptive modeling of workforce domain knowledge (2006)
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- Source
- Knowledge organization for a global learning society: Proceedings of the 9th International ISKO Conference, 4-7 July 2006, Vienna, Austria. Hrsg.: G. Budin, C. Swertz u. K. Mitgutsch
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Chen, M.; Liu, X.; Qin, J.: Semantic relation extraction from socially-generated tags : a methodology for metadata generation (2008)
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- Source
- Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
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Qin, J.: Semantic similarities between a keyword database and a controlled vocabulary database : an investigation in the antibiotic resistance literature (2000)
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- Source
- Journal of the American Society for Information Science. 51(2000) no.2, S.166-180
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Qin, J.; Hernández, N.: Building interoperable vocabulary and structures for learning objects : an empirical study (2006)
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- Source
- Journal of the American Society for Information Science and Technology. 57(2006) no.2, S.280-292
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Qin, J.; Zhou, Y.; Chau, M.; Chen, H.: Multilingual Web retrieval : an experiment in English-Chinese business intelligence (2006)
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- Source
- Journal of the American Society for Information Science and Technology. 57(2006) no.5, S.671-683
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Chau, M.; Wong, C.H.; Zhou, Y.; Qin, J.; Chen, H.: Evaluating the use of search engine development tools in IT education (2010)
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- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.2, S.288-299
