Download Models and Algorithms for High-Performance Distributed Data Mining

Call for Papers
Models and Algorithms for
High-Performance Distributed Data
Mining
a Special Issue of Journal Parallel and Distributed
Computing
Editor: Alfredo Cuzzocrea, PhD
Elsevier
Download the CFP in PDF
[Aim and Scope | Schedule | Submission Guidelines and Instructions]
Aim and Scope
Distributed Data Mining is well-understood as a resource-intensive and timeconsuming task which is devoted to extract patterns and regularities from huge
amounts of distributed data sets. Classical algorithms, mostly developed in the context
of centralized environments, have already been proved to be unsuitable to the goal of
mining data in distributed settings. This not only due to conceptual and methodological
drawbacks but, most importantly, to novel challenges posed by a distributed, resourceintensive, and time-consuming processing as dictated by high-level specifications of
distributed Data Mining algorithms.
From these challenges, performance aspects of Distributed Data Mining is now
recognized as one of the most attracting topics for the Data Mining research community,
even with respect to next-generation computational platforms (e.g., Clouds, Grids, SOA
Architectures) and paradigms (e.g., Peer-to-Peer, Map-Reduce, Service-Oriented
Computing). Emerging application scenarios like Social Networks play as well the role
of interesting contexts that may stimulate further investigation in this field.
In Distributed Data Mining models and algorithms, high-performance is not only an
architecture-and-resource--oriented matter, but also it involves in designing innovative
models, algorithms and techniques capable of dealing, from a side, with the difficulties
posed by so-challenging distributed environments and, from the other side, with the
conceptual Data Mining tasks codified within Distributed Data Mining algorithms, which
may turn to be inherently hard.
With these goals in mind, the special issue “Models and Algorithms for HighPerformance Distributed Data Mining” of JPDC will cover theoretical as well as practical
aspects of high-performance Data Mining in distribute environments, with emphasis on
both sophisticated theoretical-models-and-methodologies and pragmatic algorithms.
Topics of interest for the special issue include but are not limited to the following list:
• foundations of high-performance distributed data mining;
• high-performance distributed data mining models;
• high-performance distributed data mining methodologies;
• high-performance distributed data mining techniques;
• high-performance distributed data mining algorithms;
• scalable disk-based models for high-performance distributed data mining;
• scalable disk-based algorithms for high-performance distributed data mining;
• multi-core models for high-performance distributed data mining;
• multi-core algorithms for high-performance distributed data mining;
• cluster-based models for high-performance distributed data mining;
• cluster-based algorithms for high-performance distributed data mining;
• grid-based models for high-performance distributed data mining;
• grid-based algorithms for high-performance distributed data mining;
• cloud-based models for high-performance distributed data mining;
• cloud-based algorithms for high-performance distributed data mining;
• SOA-based models for high-performance distributed data mining;
• SOA-based algorithms for high-performance distributed data mining;
• P2P-oriented high-performance distributed data mining;
• Map-Reduce-based high-performance distributed data mining;
• Service-oriented high-performance distributed data mining;
• high-performance distributed data mining in innovative contexts like streams, sensors,
mobile environments and social networks.
Schedule
Submission of full papers: July 25, 2011
First decision notification: July 30, 2011
Submission of revised papers: September 15, 2011
Final decision notification: October 30, 2011
Final materials to Elsevier: December 30, 2011
Estimated publication date: 2012
Submission Guidelines and Instructions
All manuscripts will be rigorously refereed by at least three reviewers among people of
widely-recognized expertise. Submission of a manuscript to this special issue implies
that no similar paper is already accepted or will be submitted to any other conference
or journal.
Author guidelines for preparation of manuscript can be found at:
http://www.elsevier.com/locate/jpdc
All manuscripts and any supplementary material should be submitted through Elsevier
Editorial System (EES). Authors must select “Special Issue: Dist. Dat. Min.”
when they reach the “Article Type” step in the submission process. The EES website
for JPDC is available at: http://ees.elsevier.com/jpdc/
For more information, please contact Alfredo Cuzzocrea at
[email protected]