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BigMine 2016 : 5th International Workshop on Big Data, Streams, and Heterogeneous Source Mining KDD 2016 Workshop


When Aug 14, 2016 - Aug 14, 2016
Where San Francisco, California
Submission Deadline May 27, 2016

Call For Papers


Big Data Mining (KDD BigMine-16)
5th International Workshop on Big Data, Streams and Heterogeneous
Source Mining: Algorithms, Systems, Programming Models and
Applications (BigMine-16) - a KDD2016 Workshop

KDD2016 Conference Dates: August 13-17, 2016
Workshop Date: August 14, 2016
San Francisco, California


Papers due: May 27th 23:59PM Pacific Standard Time
Acceptance notification: June 13, 2016
Workshop Final Paper Due: July 1, 2016


The goal of the workshop is to provide a forum to bring together
researchers and practitioners to discuss important research questions
and practical challenges in big data mining and related areas. We invite
submission of papers describing innovative research on all aspects of
big data mining, stream mining, knowledge discovery, data science and
analytics. Novel ideas, controversial issues, open problems, comparisons
of competing approaches, representation of alternative viewpoints, and
discussions are all strongly encouraged.

Papers emphasizing theoretical foundations, algorithms, systems,
applications, language issues, data storage and access, architecture are
particularly encouraged. Work-in-progress papers, demos, position and
visionary papers are also welcome.

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


Examples of topics of interest include

* Scalable, Distributed and Parallel Algorithms
* New Programming Model for Large Data beyond Hadoop/MapReduce,
Spark, 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
* Classification and Regression in Data Streams
* 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.


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

Proceedings will be published as a dedicated volume of the JMLR Workshop
and Conference Proceedings. This year we are accepting papers in two
formats. Either 16 pages for regular papers (i.e., as standard KDD
papers), or 4-6 pages for short papers. See the website for more
information regarding paper preparation.


* Wei Fan, Baidu Research Big Data Lab
* Albert Bifet, Telecom-ParisTech
* Jesse Read, Telecom-ParisTech
* Qiang Yang, Hong Kong University of Science and Technology
* Philip Yu, University of Illinois at Chicago

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