SCOPE:
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Machine learning and data mining have been playing an increasing role in many real scenarios, such as web mining, language processing, image search, financial engineering, etc. In these application domains, data are surpassing the scale of terabyte in an ever faster pace, but the techniques for processing and mining them often lag behind in far too many aspects. To deal with billions of web pages, images, transaction records and capacity-intensive audio and video data stream, machine learning and data mining techniques and their underlying computing infrastructure are facing great challenges.

In this SMLA workshop we are willing to bring together researchers and practitioners for getting advancement in scalable machine learning and applications. On one hand we expect works on how to dramatically empower existing machine learning and data mining methods via grid/cloud or other novel computing models. On the other hand we value the effort of building or extending machine learning and data mining methods that are scalable to huge datasets.

Papers can be related to any subset of the following topics, or any unconventional direction to scale up machine learning and data mining methods:

-- Cloud Computing
-- Large Scale Data Mining
-- Fast Support Vector Machines
-- Data Abstraction, Dimension Reduction
-- User Personalization and Recommendation
-- Natural Language Processing
-- Ontology and Semantic Technologies
-- Parallelization of Machine Learning Methods
-- Fast Machine Learning Model Tuning and Selection
-- Large Scale Webpage Topic, Genre, Sentiment Classification
-- Financial Engineering


PAPER SUBMISSION:
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Authors are invited to submit manuscripts reporting original unpublished research and recent developments in the topics related to the workshop. The length of the papers should not exceed 6 pages + 2 pages for overlength charges (IEEE Computer Society Proceedings Manuscripts style: two columns, single-spaced), including figures and references, using 10 fonts, and number each page. Papers should be submitted electronically in PDF format by sending it as an e-mail attachment to Zhili Wu (z.wu@leeds.ac.uk). All papers will be peer reviewed and the comments will be provided to the authors. The accepted papers will be published together with those of other CIT'10 workshops by the IEEE Computer Society Press.

Distinguished selected papers, after further extensions, will be published in CIT 2010's special issues of the following prestigious SCI-indexed journals:

-- The Journal of Supercomputing – Springer
-- Journal of Computer and System Sciences – Elsevier
-- Concurrency and Computation: Practice and Experience - John Wiley & Sons