BigMine 2013 : Big Data Mining Workshop at KDD13

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Erheng Zhong

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Jun 2, 2013, 9:52:58 PM6/2/13
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Big Data Mining (BigMine-13) 
2nd International Workshop on Big Data, Streams and Heterogeneous 
Source Mining: Algorithms, Systems, Programming Models and 
Applications (BigMine-13) - a KDD2013 Workshop 

KDD2013 Conference Dates: August 11-14, 2013 
BigMine-13 Workshop Date: Aug 11, 2013 
Chicago, USA 

http://www.bigdata-mining.org 

Key dates: 
Paper Submission deadline: June 6th, 2013, 23:59PM Pacific Standard Time 
Acceptance notification: June 25, 2013 
Workshop Final Paper Due: July 2, 2013 
Workshop: August 11, 2013 

Paper submission and reviewing will be handled electronically. Authors 
should consult the submission site 
(http://bigdata-mining.org/submission/) for full details regarding 
paper preparation and submission guidelines. 

Papers submitted to BigMine-13 should be original work and 
substantively different from papers that have been previously 
published or are under review in a journal or another 
conference/workshop. 

Following KDD main conference tradition, reviews are not double-blind, 
and author names and affiliations should be listed. 

We invite submission of papers describing innovative research on all 
aspects of big data mining. 

Examples of topic of interest include 

- Scalable, Distributed and Parallel Algorithms 
- New Programming Model for Large Data beyond Hadoop/MapReduce, 
Storm, streaming languages 
- Mining Algorithms of Data in non-traditional formats 
(unstructured, semi-structured) 
- Applications: social media, Internet of Things, Smart Grid, 
Smart Transportation Systems 
- Streaming Data Processing 
- Heterogeneous Sources and Format Mining 
- Systems Issues related to large datasets: clouds, streaming 
system, architecture, and issues beyond cloud and streams. 
- Interfaces to database systems and analytics. 
- Evaluation Technologies 
- Visualization for Big Data 
- Applications: Large scale recommendation systems, social media 
systems, social network systems, scientific data mining, 
environmental, urban and other large data mining applications. 

Papers emphasizing theoretical foundations, algorithms, systems, 
applications, language issues, data storage and access, architecture 
are particularly encouraged. 

We welcome submissions by authors who are new to the data mining 
research community. 

Submitted papers will be assessed based on their novelty, technical 
quality, potential impact, and clarity of writing. For papers that 
rely heavily on empirical evaluations, the experimental methods and 
results should be clear, well executed, and repeatable. Authors are 
strongly encouraged to make data and code publicly available whenever 
possible. 

Top-quality papers accepted and presented at the workshop after 
careful revisions by the authors, reviewed by original PC members and 
chairs will be recommended to ACM TIST, ACM TKDD, IEEE Intelligent 
Systems or IEEE Computer for fast publication, depending on relevance 
of the topic.
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