Scalable Uncertainty Management: Second International Conference, SUM 2008, Naples, Italy, October 1-3, 2008, Proceedings (Lecture Notes in Computer Science, 5291)

Verlag

Springer

Erscheinungsjahr

2008

Sprache

Englisch

ISBN-10

3540879927

ISBN-13

9783540879923

Einband

Softcover

Zustand

New

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Inhaltsangabe

Originally,managinguncertainty and inconsistencyhas especiallybeen explored in the ?eld of arti?cial intelligence. During recent years, particularly with the availabilityofmassiveamountsofdataindi?erentrepositoriesandthepossibility of integrating and exploiting these data, technologies for managing uncertainty andinconsistencyhavestartedtoplayakeyroleindatabasesandtheWeb.Some of the most prominent of these technologies are probably the ranking algorithms behind Web search engines. Techniques for handling uncertainty and incons- tency are expected to play a similarly important role in the Semantic Web. The annual International Conference on Scalable Uncertainty Management (SUM) hasgrownout ofthisverylargeinterestonmanaginguncertaintyand- consistency in databases,the Web, the Semantic Web, and arti?cial intelligence. Theconferenceaimsat bringingtogether allthoseinterestedin the management of large volumes of uncertainty and inconsistency in these areas. The First - ternational Conference on Scalable Uncertainty Management (SUM 2007) was held in Washington DC, USA, October 10-12, 2007. This volume contains the papers presented at the Second International C- ference on Scalable Uncertainty Management (SUM 2008), which was held in Naples, Italy, October 1-3, 2008. It contains 27 technical papers, which were selected out of 42 submitted papers in a rigorous reviewing process, where each paper wasreviewedby at leastthree ProgramCommittee members.The volume also contains extended abstracts of the three invited tutorials/talks.

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This book constitutes the refereed proceedings of the Second International Conference on Scalable Uncertainty Management, SUM 2008, held in Naples, Italy, in Oktober 2008.

The 27 revised full papers presented together with the extended abstracts of 3 invited talks/tutorials were carefully reviewed and selected from 42 submissions. The papers address artificial intelligence researchers, database researchers, and practitioners to demonstrate theoretical techniques required to manage the uncertainty that arises in large scale real world applications and to cope with large volumes of uncertainty and inconsistency in databases, the Web, the semantic Web, and artificial intelligence in general.

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