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The Fifth International Workshop on

Mining Multiple Information Sources (MMIS-11)

In conjunction with The IEEE International Conference on Data Mining (ICDM-11), December 11, 2011, Vancouver, Canada

Introduction

As data collection channels and means become more and diverse, many real-world data mining tasks can easily acquire multiple data sets from various information sources. Compared to single-source mining problems in which all the data for a mining task are in the same pattern representation and are assumed to be drawn from the identical distribution, a multi-source mining problem is built on multiple information sources which have different contributions to the target task and can complement one another to boost the performance. To better leverage multiple information sources, integrating and transferring knowledge among multiple data sets has become a crucial step in data mining.

Topics of Interest

Representative issues to be addressed include but are not limited to:

1.     Transfer learning from multiple information sources

2.     Pattern correlation and differentiation in different data sources

3.     Integrative and cooperative mining

4.     Data integration and harnessing complex data relationship

5.      Multi-source data mining applications and case studies

 

 

Important Dates

August 5 August 15, 2011: Due date for full papers

September 20, 2011: Notification of acceptance

October 14, 2011: Camera-ready of accepted papers

December 11, 2011: Workshop date

 

Paper Submission

A maximum of 8 pages in ICDM-11 format. The paper submission site for MMIS-11 is here.

 

Workshop Co-Organizers

Bin Li

University of Technology, Sydney (UTS), Australia

Xingquan Zhu

University of Technology, Sydney (UTS), Australia

Qiang Yang

Hong Kong University of Science & Technology, Hong Kong