The Second Workshop on Management and mining Of UNcertain Data (MOUND 2010)

The Second Workshop on Management and mining Of UNcertain Data

(MOUND 2010)
In conjunction with ICDE 201 0

March 1, 2010, Long Beach, California, USA

Program Chairs

Heng Tao Shen

The University of Queensland

Graham Cormode

AT&T Labs-Research

PC Members

Selcuk Candan

Arizona State University

Feifei Li

Florida State University

Xue Li

University of Queensland

George Kollios

Boston University

Flip Korn

AT&T Labs-Research

Dan Olteanu

Oxford University

Christopher Re

University of Washington

Anish Das Sarma

Stanford University

Ke Yi

Hong Kong University of Science and Technology

Jeffrey Yu

Chinese University of Hong Kong

Anthony K. H. Tung

National University of Singapore

Alfredo Cuzzocrea

University of Calabria

Steering Committee

Lei Chen

Hong Kong University of Science and Technology

Xuemin Lin

The University of New South Wales

Reynold Cheng

Hong Kong University

Sunil Prabhakar

Purdue University

Workshop Goals

Recently, uncertain data management and mining has become a critical issue in many real applications, such as sensor data monitoring, location-based services, object identification, and moving object search. Unlike exact data, uncertain data are often represented as a set of discrete samples or a probability density function, which presents new challenges for analyzing, querying, and mining the uncertain data effectively and efficiently. Following the success of the First International workshop on Management and mining Of UNcertain Data (MOUND) 2009, the Second MOUND 2010 will continue to investigate key issues related to the data management and mining over uncertain data. Specifically, this forum welcomes contributions that explore uncertain data management issues such as data representation, various types of queries, and indexes. Additionally, the workshop hopes to attract work that studies the new data mining techniques of data cleaning, clustering, and classification over uncertain data including sensor data, location data, web and multimedia data.

Topics of Interest

With respect to the database management, many key issues need to be investigated:

Uncertain data representation
Queries and indexes over uncertain data
Building and optimizing systems for uncertain data
Management of uncertain data streams

For data mining over uncertain data, the major focuses are:

Uncertain data cleaning
Clustering, classification and other mining over uncertain data
Tagging and annotation over uncertain data

The workshop is particularly interested in attracted new and innovative contributions on perspectives and tools in uncertain data management that can stimulate discussion and thinking.

Paper Submission

High quality research papers in the relevant areas are solicited. Original papers exploring new directions will receive especially careful consideration. Papers that have already been accepted or are currently under review for other conferences or journals will not be considered for MOUND10. Paper submissions should be limited to a maximum of 8 pages in the camera-ready format of ICDE10. All papers will be reviewed by the Program Committee on the basis of technical quality, relevance to data mining, originality, significance, and clarity. All accepted workshop papers will be included in a proceeding published by the IEEE Computer Society Press.

Please submit your papers using the following submission site: https://cmt.research.microsoft.com/MOUND201 0

For any questions, please email to: shenht@itee.uq.edu.au or graham@research.att.com.

Important Dates

Paper Submission Due: December 1, 2009
Acceptance Notification: December 21, 2009
Camera Ready: January 6, 2010

Sponsorship

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