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- This is the report of the W3C Uncertainty Reasoning for the World Wide Web Incubator Group (URW3-XG) as specified in the Deliverables section of its charter. In this report we present requirements for better defining the challenge of reasoning with and representing uncertain information available through the World Wide Web and related WWW technologies. Specifically the report: * identifies and describes situations on the scale of the World Wide Web for which uncertainty reasoning would significantly increase the potential for extracting useful information, * identifies methodologies that can be applied to these situations and the fundamentals of a standardized representation that could serve as the basis for information exchange necessary for these methodologies to be effectively used, * includes a set of use cases illustrating conditions under which uncertainty reasoning is important, * provides an overview and discusses the applicability to the World Wide Web of prominent uncertainty reasoning techniques and the information that needs to be represented for effective uncertainty reasoning to be possible, * includes a bibliography of work relevant to the challenge of developing standardized representations for uncertainty and exploiting them in Web-based services and applications. The report identifies various areas which require further investigation and debate.
- Abstract. The envisioned Semantic Web aims to provide richly annotated and explicitly structured Web pages in XML, RDF, or description logics, based upon underlying ontologies and thesauri. Ideally, this should enable a wealth of query processing and semantic reasoning capabilities using XQuery and logical inference engines. However, we believe that the diversity and uncertainty of terminologies and schema-like annotations will make precise querying on a Web scale extremely elusive if not hopeless, and the same argument holds for large-scale dynamic federations of Deep Web sources. Therefore, ontology-based reasoning and querying needs to be enhanced by statistical means, leading to relevanceranked lists as query results. This paper presents steps towards such a “statistically semantic”Web and outlines technical challenges.We discuss how statistically quantified ontological relations can be exploited in XML retrieval, how statistics can help in making Web-scale search efficient, and how statistical information extracted from users’ query logs and click streams can be leveraged for better search result ranking. We believe these are decisive issues for improving the quality of next-generation search engines for intranets, digital libraries, and the Web, and they are crucial also for peer-to-peer collaborative Web search.
- Bayesian Networks are probabilistic structured representations of domains which have been applied to monitoring and manipulating cause and effects for modelled systems as disparate as the weather, disease and mobile telecommunications networks. Although useful, Bayesian Networks are notoriously difficult to build accurately and efficiently which has somewhat limited their application to real world problems. Ontologies are also a structured representation of knowledge, encoding facts and rules about a given domain. This paper outlines an approach to harness the knowledge and inference capabilities inherent in an ontology model to automate the construction of Bayesian Networks to accurately represent a domain of interest. The approach was implemented in the context of an adaptive, self-configuring network management system in the telecommunications domain. In this system, the ontology model has the dual function of knowledge repository and facilitator of automated workflows and the generated BN serves to monitor effects of management activity, forming part of a feedback look for self-configuration decisions and tasks.
- "a special issue of Nature examines the cultural and technical hurdles that can get in the way of good intentions"
- author: Ole Winther, Technical University of Denmark
publications (hide)739
- (2010)cite arxiv:1006.2761.
- BMC Bioinformatics, 11 (1): 255 (2010)
- BMC Bioinformatics, 11 (1): 292 (2010)
- (2010)cite arxiv:1006.0408.
- Nucleic Acids Res, 31 (19): 5789-5804 (October 2003)
- Nucl. Acids Res., 37 (suppl_1): D417-422 (2009)
- PAKDD, volume 5476 of Lecture Notes in Computer Science, page 628-636. Springer, (2009)
- (2010)
- v11, (1771)
- v11, (1709)
- v11, (1663)
- v11, (1643)
- BMC Bioinformatics, 11 (1): 271 (2010)
- Proceedings of the 6th International Semantic Web Conference (ISWC), volume 4825 of Lecture Notes in Computer Science, page 722--735. Springer, (2008)
- Proceedings Thirteenth Conference on Uncertainty in Artificial Intelligence (UAI), page 302--313. (1997)
- Drug Discov Today, 10 (13): 937-942 (July 2005)
- Technical Report, SMI-2001-0880. Stanford Medical Informatics, Stanford, (2001)
- CIMCA '05: Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce Vol-1 (CIMCA-IAWTIC'06), page 457--463. Washington, DC, USA, IEEE Computer Society, (2005)
- Soft Computing in Ontologies and Semantic Web, (2006)
- Journal of Artificial Intelligence Research, (1994)
- European Semantic Web Conference (ESWC), volume 3532 of Lecture Notes on Computer Science, page 500-514. Springer, (2005)
- Namespace document, (January 2010)
- W3C Working Group Note, (Aug 28, 2008)
- W3C Recommendation, World Wide Web Consortium, (Oct 27, 2009)
- W3C Recommendation, World Wide Web Consortium, (Feb 10, 2004)
- W3C Working Group Note, World Wide Web Consortium, (Apr 12, 2006)
- W3C Recommendation, World Wide Web Consortium, (Feb 10, 2004)
- The Description Logic Handbook. Theory, Implementation and Applications, Cambridge University Press, (2003)
- (2003)
- (1998)
- Knowledge Acquisition, 5 (2): 199-221 (1993)
- Scientific American, 284 (5): 34--43 (2001)
- PLoS Comput Biol, (December 2007)
- (2010)
- (2010)
- BMC Bioinformatics, 11 (1): 229 (2010)
- BMC Bioinformatics, 11 (1): 267 (2010)
- Brief Bioinform, 11 (3): 278-289 (2010)
- W3C Recommendation, World Wide Web Consortium, (Feb 10, 2004)
- International Journal of Human and Computer Studies, (1995)
- (2003)
- Science, 303 (5659): 799-805 (2004)
- The Description Logic Handbook: Theoryand Implementationand and Applications, Cambridge University Press, (2003)
- (2010)cite arxiv:1005.2107 Comment:.
- BMC Bioinformatics, 11 (1): 213-213 (April 2010)
- BMC Bioinformatics, 11 (1): 191 (2010)
- Mathematical Knowledge Management, (2004)
- Principles of Knowledge Representation and Reasoning: Proceedings of the 4th International Conference (KR '94): Bonn, Germany: 1994, May, 24 - 27, page 258-269. Morgan Kaufmann Publishers, (1994)
- (2007)
- (2005)
