ABSTRACT
Richly interlinked, machine-understandable data constitutes the basis for the Semantic Web. Annotating web documents is one of the major techniques for creating metadata on the Web. However, annotation tools so far are restricted in their capabilities of providing richly interlinked and truely machine-understandable data. They basically allow the user to annotate with plain text according to a template structure, such as Dublin Core. We here present CREAM (Creating RElational, Annotation-based Metadata), a framework for an annotation environment that allows to construct relational metadata, i.e. metadata that comprises class instances and relationship instances. These instances are not based on a fix structure, but on a domain ontology. We discuss some of the requirements one has to meet when developing such a framework, e.g. the integration of a metadata crawler, inference services, document management and information extraction, and describe its implementation, viz. Ont-O-Mat a component-based, ontology-driven annotation tool.
- 1.R. Benjamins, D. Fensel, and S. Decker. KA2: Building Ontologies for the Internet: A Midterm Report. International Journal of Human Computer Studies, 51(3):687, 1999.Google ScholarDigital Library
- 2.S. Decker, D. Brickley, J. Saarela, and J. Angele. A Query and Inference Service for RDF. In Proceedings of the W3C Query Language Workshop (QL-98), http://www.w3.org/TandS/QL/QL98/, Boston, MA, December 3-4, 1998.Google Scholar
- 3.S. Decker, M. Erdmann, D. Fensel, and R. Studer. Ontobroker: Ontology Based Access to Distributed and Semi-Structured Information. In R. Meersman et al., editors, Database Semantics: Semantic Issues in Multimedia Systems, pages 351-369. Kluwer Academic Publisher, 1999. Google ScholarDigital Library
- 4.L. Denoue and L. Vignollet. An annotation tool for web browsers and its applications to information retrieval. In In Proceedings of RIAO2000, Paris, April 2000. http://www.univ-savoie.fr/ labos/ syscom/Laurent.Denoue/riao2000.doc.Google ScholarDigital Library
- 5.M. Erdmann, A. Maedche, H.-P. Schnurr, and Steffen Staab. From manual to semi-automatic semantic annotation: About ontology-based text annotation tools. In P. Buitelaar & K. Hasida (eds). Proceedings of the COLING 2000 Workshop on Semantic Annotation and Intelligent Content, Luxembourg, August 2000. Google ScholarDigital Library
- 6.H. Eriksson, R. Fergerson, Y. Shahar, and M. Musen. Automatic generation of ontology editors. In Proceedings of the 12th Banff Knowledge Acquisition Workshop, Banff, Alberta, Canada, 1999.Google Scholar
- 7.Reference description of the daml+oil (march 2001) ontology markup language, March 2001. http://www.daml.org/2001/03/reference.html.Google Scholar
- 8.T. R. Gruber. A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition, 6(2):199- 221, 1993. Google ScholarDigital Library
- 9.Siegfried Handschuh. Ontoplugins - a flexible component framework. Technical report, University of Karlsruhe, May 2001.Google Scholar
- 10.J. Heflin and J. Hendler. Searching the web with shoe. In Artificial Intelligence for Web Search. Papers from the AAAI Workshop. WS-00-01, pages 35-40. AAAI Press, 2000.Google Scholar
- 11.J. Heflin, J. Hendler, and S. Luke. Applying Ontology to the Web: A Case Study. In Proceedings of the International Work-Conference on Artificial and Natural Neural Networks, IWANN'99, 1999.Google ScholarCross Ref
- 12.Dublin Core Metadata Initiative. http://purl.oclc.org/dc/, April 2001.Google Scholar
- 13.J. Kahan, M. Koivunen, E. Prud'Hommeaux, and R. Swick. Annotea: An Open RDF Infrastructure for Shared Web Annotations. In Proc. of the WWW10 International Conference. Hong Kong, 2001. Google ScholarDigital Library
- 14.M. Kifer, G. Lausen, and J. Wu. Logical foundations of object-oriented and frame-based languages. Journal of the ACM, 42, 1995. Google ScholarDigital Library
- 15.J. Klotzbuecher. Ontowrapper. Master's thesis, University of Karlsruhe, to appear 2001.Google Scholar
- 16.N. Kushmerick. Wrapper Induction: Efficiency and Expressiveness. Artificial Intelligence, 118(1), 2000. Google ScholarDigital Library
- 17.S. Luke, L. Spector, D. Rager, and J. Hendler. Ontology-based Web Agents. In Proceedings of First International Conference on Autonomous Agents, 1997. Google ScholarDigital Library
- 18.A. Maedche and S. Staab. Ontology learning for the semantic web. IEEE Intelligent Systems, 16(2), 2001. Google ScholarDigital Library
- 19.P. Martin and P. Eklund. Embedding Knowledge in Web Documents. In Proceedings of the 8th Int. World Wide Web Conf. (WWW'8), Toronto, May 1999, pages 1403-1419. Elsevier Science B.V., 1999. Google ScholarDigital Library
- 20.MUC-7 - Proceedings of the 7th Message Understanding Conference. http://www.muc.saic.com/, 1998.Google Scholar
- 21.S. Staab and A. Maedche. Knowledge portals - ontologies at work. AI Magazine, 21(2), Summer 2001.Google Scholar
- 22.S. Staab, A. Maedche, and S. Handschuh. Creating metadata for the semantic web: An annotation framework and the human factor. Technical Report 412, Institute AIFB, University of Karlsruhe, 2001.Google Scholar
- 23.Ka-Ping Yee. CritLink: Better Hyperlinks for the WWW, 1998. http://crit.org/ ping/ht98.html.Google Scholar
Index Terms
- CREAM: creating relational metadata with a component-based, ontology-driven annotation framework
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