Big Data Mining
1st International Workshop on Big Data, Streams and Heterogeneous
Source Mining: Algorithms, Systems, Programming Models and
Conference Dates: August 12-16, 2012
Workshop Date: Aug 12, 2012
Papers due: May 9, 2012
Acceptance notification: May 23, 2012
Workshop Final Paper Due: June 8, 2012
Workshop Proceedings Due: June 15, 2012
Paper submission and reviewing will be handled electronically. Authors
should consult the submission site (http://
http://big-data-mining.org/submission/) for full details regarding
paper preparation and submission guidelines.
Papers submitted to BigMine-12 should be original work and
substantively different from papers that have been previously
published or are under review in a journal or another
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
1. Scalable, Distributed and Parallel Algorithms
2. New Programming Model for Large Data beyond Hadoop/MapReduce,
STORM, streaming languages
3. Mining Algorithms of Data in non-traditional formats (unstructured,
4. Applications: social media, Internet of Things, Smart Grid, Smart
5. Streaming Data Processing
6. Heterogeneous Sources and Format Mining
7. Systems Issues related to large datasets: clouds, streaming system,
architecture, and issues beyond cloud and streams.
8. Interfaces to database systems and analytics.
9. Evaluation Technologies
10. Visualization for Big Data
11. 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
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
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