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MMIS 2010 : The 4th International Workshop on Mining Multiple Information Sources

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Link: http://www.cse.fau.edu/~xqzhu/mmis/mmis-10/mmis10.html
 
When Dec 13, 2010 - Dec 13, 2010
Where Sydney, Australia
Submission Deadline Jul 23, 2010
Notification Due Sep 20, 2010
Final Version Due Oct 11, 2010
Categories    data mining
 

Call For Papers

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Call for Papers

The 4th International Workshop on Mining Multiple Information Sources (MMIS)
http://www.cse.fau.edu/~xqzhu/mmis/mmis-10/mmis10.html
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As data collection sources and channels continuous evolve, mining and correlating
information from multiple information sources has become a crucial step in data mining
and knowledge discovery. Several emerging fields and applications from healthcare
informatics to environmental sciences to social computing in particular call for datamining
methodologies and approaches to deal with multi-source data.
On one hand, comparing patterns from different databases and understanding their
relationships can be extremely beneficial for these applications.
On the other hand, many data mining and data analysis tasks such as classification,
regression, and clustering, can significantly improve their performance if information
rom different sources can be properly integrated and leveraged.

The aim of this workshop is to bring together data mining experts to advance research
on integrating and mining multiple information sources, identify key research issues,
and discuss the latest results on this new frontier of data mining.
Representative issues to be addressed include but are not limited to:

Machine Learning in Multi-source Environments
+Multi-view learning, multi-task learning, transfer learning
+Ensemble learning and ensemble clustering
Information Integration and Harnessing Complex Data Relationship
+Database similarity assessment
+Automatic schema mapping and relationship discovery
+New mapping framework for multiple information sources
+Data source classification and clustering
+Data cleansing, data preparation, data/pattern selection, conflict and inconsistency resolution
Integrative and Cooperative Mining
+Model integration for heterogeneous information sources
+Mode transferring across different data domains
+Incremental and scalable data mining algorithms
Differentiation and Correlation
+Local pattern analysis and fusion
+Global pattern synthesizing and assessment
+Merging local rules for global pattern discovery
+Pattern summarization from multiple datasets
+Multi-dimensional pattern search and comparison
+Pattern comparison across multiple data sources
+Inter pattern discovery from complex data sources
Stream data mining algorithms
+Clustering and classification of data of changing distributions
+Data stream processing, storage, and retrieval systems
+Sensor networking
Interactive data mining systems
+Query languages for mining multiple information sources
+Query optimization for distributed data mining
+Distributed data mining operators in supporting interactive data mining queries

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Paper Types
We solicit two types of papers:
Research paper and Application paper (8 pages for all submissions inclusive of all references and figures).
Research papers should focus on new designs, algorithms, and solutions for mining multiple
information sources, whereas Application papers may provide frameworks and systems
related to real-world multi-source mining applications. Alternatively, the authors
can submit a data track application paper (2 pages) which purely discusses real-world
multi-source data and related research topics. A copy of multi-source data must be submitted
(through email) for verification. If there is any copyright issue related
to the submitted data, the authors should clearly mention this issue in the submission.

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Important Dates
July 23, 2010 : Submission Due Date
September 20, 2010: Notification of paper acceptance to authors
October 11, 2010: Camera-ready of accepted papers
December 13, 2010: Workshop in Sydney, Australia


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Workshop Co-Chairs

Ruoming Jin
Kent State University, USA
Xingquan Zhu
Faculty of Engineering and Information Technology, Australia
Haixun Wang
Microsoft Research Asia, China
Zoran Obradovic
Director, Information Science and Technology Center,
Computer and Information Sciences Department, Temple

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