Workshop Goals

Recently, uncertain data management and mining 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 raises new challenges on analyzing, querying, and mining the uncertain data effectively and efficiently. . The goal of the 1st workshop on Management and mining Of UNcertain Data (MOUND 2009) is to investigate key issues related to the data management and mining over uncertain data. Specifically, we would like to explore uncertain data management issues such as data representation, various types of queries, and indexes. Meanwhile, we will study the new data mining techniques on data cleaning, clustering, and classification over uncertain data.

Topics of Interest

Topics related to the data management and mining issues of uncertain data are of interest. These include, but are not limited to:
Uncertain data representation
Queries over uncertain data
Indexes on uncertain data
Uncertain streams management
Mining probabilistic databases;
Mining spatially- and temporally- uncertain data;
Mining biological data with noises;
Scalable evaluation of probabilistic queries;
Data cleansing and error function;
Mining streams of uncertain data.

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 MOUND'09. Paper submissions should be limited to a maximum of 8 pages in the IEEE 2-column format, the same as the camera-ready format (see the IEEE Computer Society Press Proceedings Author Guidelines at (http://www.computer.org/portal/pages/cscps/cps/final/icdm06.xml). 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.

For any questions, please email to: mound@cse.ust.hk

Important Dates

Paper Submission Due: October 31, 2008 9PM PT
Acceptance Notification: December 15, 2008
Camera Ready: January 9, 2009