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Guarino N, Giaretta P. 1995. Ontologies and knowledge bases: Towards a terminological clari cation. In Towards Very Large Knowledge Bases: Knowledge Building and Knowledge Sharing, Mars N (ed). IOS Press: Amsterdam. pp 25 32. Mahesh K, Nirenburg S, Cowie J, Farwell D. An Assessment of Cyc for Natural Language Processing. MCCS Report, New Mexico State University, 1996. Manov D, Kiryakov A, Popov B, Bontcheva K, Maynard D, Cunningham H. 2003. Experiments with geographic knowledge for information extraction. NAACL-HLT 2003, Canada. Workshop on the Analysis of Geographic References, May 31 2003, Edmonton, Alberta. Martin-Recuerda F, Harth A, Decker S, Zhdanova A, Ding Y, Stollberg M 2004. Deliverable D2.1 Report on requirements analysis and state-of-the-art within WP2 Ontology Management of the DIP project. https://bscw.dip.deri.ie/bscw/ bscw.cgi/0/3012 Maynard D, Tablan V, Bontcheva K, Cunningham H, Wilks Y. 2003. Multi-Source Entity recognition An Information Extraction System for Diverse Text Types. Technical report CS 02 03, University of Shef eld, Department of CS, 2003. http://gate.ac.uk/gate/doc/papers.html Meyer-Fujara J, Heller B, Schlegelmilch S, Wachsmuth I. 1994. Knowledge-level modularization of a complex knowledge base. In KI-94: Advances in Arti cial Intelligence Nebel B, Dreschler-Fischer L (eds). Springer: Berlin. pp 214 225. Kiryakov A, Popov B, Ognyanov D, Manov D, Kirilov A, Goranov M. 2004a. Semantic Annotation, Indexing, and Retrieval. To appear in Elsevier s Journal of Web Semantics, Vol. 1, ISWC2003 special issue (2), 2004. http://www.websemanticsjournal.org/ Kiryakov A, Ognyanov D, Kirov V. 2004b. D2.2: An Ontology Representation and Data Integration (ORDI) Framework. DIP project deliverable. http://dip.semanticweb.org Kiryakov A, Ognyanov D, Manov D. 2005. OWLIM A Pragmatic Semantic Repository for OWL. In Proceeding of International Workshop on Scalable Semantic Web Knowledge Base Systems (SSWS 2005), WISE 2005, 20 November, New York City, USA. Klyne G, Carroll JJ. 2004. Resource Description Framework (RDF): Concepts and Abstract Syntax. W3C recommendation 10 February, 2004. http://www.w3. org/TR/rdf-concepts/ Laboratory of Applied Ontologies, Institute of Cognitive Science and Technology, Italian National Research Council. DOLCE: A Descriptive Ontology for Linguistic and Cognitive Engineering. http://www.loa-cnr.it/DOLCE.html Noy N 2004 Representing Classes As Property Values on the Semantic Web. W3C Working Draft 21 July 2004. http://www.w3.org/TR/2004/WD-swbp-classesas-values-20040721/ Peters W (ed.). 1998. The EuroWordNet Base Concepts and Top Ontology. Version 2, Final. January 22, 1998. http://www.illc.uva.nl/EuroWordNet/corebcs/ topont.html Pinto S, Staab S, Tempich C. 2004. DILIGENT: Towards a ne-grained methodology for Distributed Loosely-controlled and evolvInG Engineering of oNTologies. In Proceedings of ECAI-2004, Valencia, August 2004. Shirky C. 2005. Ontology is Overrated: Categories, Links, and Tags. Clay Shirky s Writings About the Internet. Economics & Culture, Media & Community. http://www.shirky.com/writings/ontology_overrated.html Spark Jones K. 2004. What s new about the Semantic Web Some questions. SIGIR Forum December 2004, Volume 38 Number 2. http://www.sigir.org/forum/ 2004D-TOC.html
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ONTOLOGIES FOR KNOWLEDGE MANAGEMENT
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Terziev I, Kiryakov A, Manov D. 2004. D 1.8.1. Base upper-level ontology (BULO) Guidance, report EU-IST Integrated Project (IP) IST-2003-506826 SEKT), 2004. http://proton.semanticweb.org/D1_8_1.pdf Williams S. 2002. The Associative Model of Data. Second Edition, Lazy Software, Ltd. ISBN: 1-903453-01-1. http://www.lazysoft.com
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8.1. INTRODUCTION
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Previous chapters have described the core technologies which underpin the Semantic Web. This chapter describes how these semantic web technologies can provide an improved user experience, through enhanced tools for accessing knowledge. The domain model implicit in an ontology can be used as a unifying structure to give information about a common representation and semantics. Once this unifying structure for heterogeneous information sources exists, it can be exploited to improve the performance of knowledge access tools. In this chapter, we look at the application of such technology to three aspects of knowledge access: semantic search and browse tools; the generation of information expressed in natural language from formal (ontological) knowledge bases (natural language generation); and the intelligent delivery of information to multiple end-user information appliances (device independence). Finally, we describe SEKTAgent, a knowledge management tool which illustrates the use of all three of these technologies.
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