Big Data Mining (BigMine-12)

Call for Papers

Big Data Mining (BigMine-12)
1st International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications (BigMine-12) – a KDD2012 Workshop

KDD2012 Conference Dates: August 12-16, 2012
BigMine-12 Workshop Date: Aug 12, 2012
Beijing, China

Key dates:
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 ( 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 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