SUM 2007
Oct 10-12, 2007
Washington DC area

International Conference on Scalable

Uncertainty Management

(SUM 2007)

Oct 10-12, 2007
Washington DC Area



Important Dates

Call for Papers

Program Committee

Submission Info


(Jul 5) Registration is now open

The conference program is now available

The conference proceedings are now available online through SpringerLink

There is now intense interest in both the Artificial Intelligence community and in the Database community on managing uncertainty and inconsistency in databases. However, researchers in AI may not necessarily be aware of database concerns and conversely, database researchers may not always be aware of AI concerns and past contributions. There is no single, unified research community that addresses the problems of managing huge amounts of uncertainty and inconsistency in a semantically defendable manner when huge amounts of data are being processed.

In order to help create such a community, we start a 3-day international conference on "Scalable Uncertainty Management" (SUM). The first SUM conference will be held in the Washington DC area. We expect this conference to continue as an annual series. The conference is intended to focus on the following broad areas:

1.     Uncertainty models, probabilistic logics, fuzzy logics, annotated logics, possibilistic logics, Bayesian models, Markov models and others.

2.     Inconsistency logics. multiple valued inconsistency models, default and preferential logics, logics of inconsistency, paraconsistent logics.

3.     Database algebras and calculi. extensions of the relational, object oriented, semi-structured, semantic web and other related algebras and calculi to incorporate one or more uncertainty/inconsistency models.

4.     Scalable database systems incorporating uncertainty. Query optimization techniques, indexing methods, aggregate query processing techniques, view management techniques in databases that include uncertainty and inconsistency management.

5.     Spatial, temporal, mobile and multimedia databases incorporating uncertainty. Techniques to scalably reason about the inconsistency and/or uncertainty that is inherently present in temporal, geospatial, mobile and multimedia databases.

6.     Implementations. Descriptions of implemented systems with a focus on experimental methods (and perhaps a mix of heuristic and exact algorithms) that show scalable performance.

7.     Applications. Novel applications of implemented systems that reason about either large amounts of uncertainty or inconsistency in large, real world data sets. Applications can span areas such as computer vision, audio and speech processing, to industrial applications and case studies of how companies handled these problems.

General Chair:

Didier Dubois (Univ. Paul Sabatier, France)

Program Chairs:

Henri Prade (Univ. Paul Sabatier, France)

V.S. Subrahmanian (Univ. of Maryland, USA)

Publicity Chair:

Andrea Pugliese (Univ. of Calabria, Italy)