Current approaches for mining big data such as streaming have fundamental limitations on the kind of mining that can be performed. However, machines with hundreds of GB of RAM are available nowadays. This workshop will focus on novel data mining algorithms that use RAM effectively by mining data stored in compact or compressed formats. A key underlying theme will be the application of compressed and succinct data structures including FM-index, wavelet trees, compressed suffix arrays, XBW etc. and their application to data mining.
This workshop is supported by JST ERATO Minato Project.
The workshop invites submissions on aspects of data mining that focus on in-core mining of large data sets including but not limited to:
Papers emphasizing theoretical foundations, algorithms, novel use of data compression, and applications are particularly welcome. Submitted papers will be assessed based on the novelty of approach, scientific rigour, relevance to the themes of the workshop and clarity of writing. For papers that rely heavily on empirical evaluations, the experimental methods and results should be clear, well executed, and repeatable. Submitting authors are strongly encouraged to make data and code available whenever possible.
Papers submitted to this workshop must not be under review or accepted for publication elsewhere. All submitted papers will be reviewed and selected by the program committee on the basis of originality, technical quality, relevance to the workshop and presentation quality. Accepted papers will be included in the ICDM 2013 Workshop Proceedings published by IEEE Computer Society Press.
Papers must be limited to a maximum of 8 pages, and follow the IEEE ICDM format requirement. For paper formatting instructions, please visit: http://www.computer.org/portal/web/cscps/formatting.
All papers should be submitted via the ICDM 2013 Workshop submission system.
See ICDM 2013 website about the registration for this workshop.