Call for Book Chapters: Data Mining in Time Series and Streaming Databases
Publisher: World Scientific,
Singapore.
Prof. Mark Last, Ben-Gurion
University of the Negev, Israel. Email: mlast@bgu.ac.il.
Prof. Abraham Kandel, Florida
International University, FL, USA. Email: Akandel@cis.fiu.edu.
Prof. Horst Bunke, University of
Bern, Switzerland. Email: bunke@inf.unibe.ch.
Proposal Submission: February
15, 2016
Notification of Proposal
Acceptance: February 28, 2016
Full Chapter Submission: June
30, 2016
Notification for chapter
acceptance: August 31, 2016
Submission of the camera-ready
chapters: October 31, 2016
Anticipated book publication:
First quarter of 2017
Traditional data mining and time
series analysis methods are designed to deal with “static” data, which is
stored entirely in a database system and where the patterns of interest do not
change significantly over time. Many data mining algorithms even ignore the arrival
ordering of observations as irrelevant to the knowledge discovery process. With
these assumptions being sufficiently accurate in some applications, an
increasing amount of systems and sensors produce massive, high-speed streams of
ever-changing data generated by dynamic processes. The high volume and velocity of such data
streams require real time or near real time processing due to the volatility of
the incoming observations, which can be stored for a limited, if any, time
only. Dynamic data streams can be found in a variety of fields including
weather monitoring, traffic control, stock trading, cyber security, and, more
recently, Internet of Things (IoT). Mining real-world
time series and streaming data creates a need for new technologies and
algorithms, which are still being developed and tested by data scientists
worldwide.
The purpose of this volume is to
present the most recent advances in pre-processing, mining, and utilization of streaming
data that is generated by modern information systems. Mining big time series and data streams introduces
new aspects and challenges to the tasks of data mining and knowledge
discovery. Examples of these new
challenges include: finding the most efficient representation of streaming
data, developing privacy-preserving methods for data stream mining, incremental
pre-processing of continuous time series and data streams in parallel to the
data mining process, handling delayed information, mining entity-related time
series, and developing online monitoring systems.
Submissions are solicited on the following
topics, but not limited to:
·
Preprocessing streaming data for data mining
·
Privacy-preserving data stream mining
·
Time series representation, summarization, and indexing
·
Feature extraction from temporal data
·
Similarity measures and clustering of time series
·
Induction of temporal patterns and rules
·
Classification and forecasting from streaming data
·
Distributed processing of streaming data
·
Resource-aware methods for mining big time series and data
streams
·
Entity stream mining and event history analysis
·
Handling incomplete, delayed and/or costly information
·
Online segmentation methods
·
Concept drift detection and change detection in evolving data
streams
·
Anomaly detection in univariate and multivariate time series
·
Mining fuzzy time series
·
Multi-criteria evaluation of data stream mining systems
·
Detailed descriptions of real-world projects in mining streaming
data
·
Software tools for mining time series and data streams
PROPOSAL SUBMISSION: Prospective
authors should submit a chapter proposal by February 15, 2016 including the
following information:
·
Title of the contribution/chapter
·
Name of author, co-authors, institution, email-address
·
Preliminary abstract of the proposed article (150 – 250 words)
PROPOSAL ACCEPTANCE NOTIFICATION: Authors will be notified by February
28, 2016 about the status of their proposals.
FULL CHAPTER SUBMISSION:
Chapters have to be 20-25 pages length and will be reviewed by two/three expert
reviewers to ensure the quality of the volume. All contributions must be
original work, which have not been published elsewhere nor are currently under
review for any other publication. The deadline of submission is June 30, 2016.
CHAPTER ACCEPTANCE NOTIFICATION:
Authors of submitted chapters will be notified by August 31, 2016 about their
acceptance/rejection.
CAMERA-READY CHAPTER DUE:
Camera-ready version of the accepted chapters incorporating revisions (if any)
is expected to be submitted by October 31, 2016.
BOOK PUBLICATION: The book is
anticipated to appear in print in the first quarter of 2017.
Inquiries and submissions can be
forwarded to Prof. Mark Last (mlast@bgu.ac.il).
Please use the subject "Data Streams Book".