PRICAI 2012 Special Session on Scalable Big Data Mining
Data have become a torrent flowing in many important areas. Big data refers to datasets whose size is beyond the ability of current state-of-the art analytic tools. Streaming data is an specific approach to deal with big data that is evolving and changing. Parallelization is another scalable approach to mine large quantities of data.
This special session aims to provide an opportunity for researchers to share their ideas and efforts in building new algorithms, methods and software for dealing with big data, static or evolving streams.
Topics of interest include but are not limited to:
- Evolving Stream Mining
- Large-scale Machine Learning
- Distributed System Platforms: Hadoop, S4, Storm
- Evaluation Methodologies
- Visualization Techniques for Big Data
- Social Media Mining
Important Dates
PRICAI 2012 Special Session on Scalable Big Data Mining deadlines are:
| Paper Submission Deadline: | March 31, 2012 |
| Paper Acceptance Notification: | May 15, 2012 |
| Camera-Ready Paper + Copyright Submission: | May 21, 2012 |
| Conference: | Sept 5 - 7, 2012 |
Organizers
- Wei Fan (IBM T.J.Watson Research, USA)
- Xiatian Zhang (Business Intelligence Center Tencent, China)
- Albert Bifet (University of Waikato, New Zealand)
- Geoff Holmes (University of Waikato, New Zealand)
Paper Preparation and Formatting
Papers for this special session should be prepared in accordance with the PRICAI 2012 requirements.
Proceedings will be published by Springer as a volume of LNAI series. All papers should be submitted electronically using the conference management tool in PDF format and formatted using Springer's manuscript submission guideline:
http://www.springer.de/comp/lncs/authors.htmlSubmitted papers should not exceed 12 pages. Submitted papers should not be under review or submitted for publication elsewhere during the review period. Papers to be submitted via EasyChair at:
https://www.easychair.org/conferences/?conf=pricai2012Please remember to submit the paper to the track corresponding to the "Special Session on Scalable Big Data Mining" so that the submission system recognises your paper as part of this special session.