MIKE 2017 – Call for Papers
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The MIKE 2017 Program Committee invites submissions of original theoretical research, applied
research and deployed application papers on all aspects of Learning Algorithms, Data / Text
Mining and Knowledge discovery techniques for the main technical program.
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Deadlines:
Workshop Proposal June 30, 2017
Full Paper: August 20, 2017, 11:59 PM PST
Notification: September 15, 2017
Camera Ready Copy and
Registration Deadline: September 25, 2017 (11:59 PM PST)
Conference: December 13 – 15, 2017
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Submission Topics:
The MIKE 2017 Program Committee invites submissions of original theoretical research, applied research and deployed application papers on all aspects of Data Mining, Learning theory and Knowledge Discovery. Example submission areas include, but are not limited to:
Artificial intelligence
Automated reasoning and inference
Cognitive aspects of AI
Common-sense reasoning
Knowledge representation
Multi-agent systems
Reasoning under uncertainty or imprecision
Association rule learning
Artificial neural networks
Deep / Machine learning
Representation learning
Similarity and metric learning
Sparse dictionary learning
Rule-based machine learning
Learning classifier systems
Predicting Material Properties
Predicting Mechanical Properties
Thermal Properties of Fluids
Design Materials
Fuzzy Logic / Fuzzy Systems
Computational Intelligence
Data Mining and Information Retrieval
Data visualisation
Behaviour analytics
Information retrieval and extraction
Big data infrastructure and visualisation
Scalable computing and high-performance computing for big data
Computational intelligence based theories and methods
Statistical and mathematical techniques
Data characteristics and complexities
Bioinformatics, computational biology, health and medical analytics
Image Analysis, Pattern Recognition and Computer Vision
Visual search
3D computer vision
Vision for graphics / robotics / web
Computational photography, sensing and display
Image and video analysis
Motion and tracking
Content-based retrieval of image and video
Face and gesture recognition
Speech / Signal Processing
phonetics and phonology; syntax; cognitive aspects
Speech signal analysis / Speech recognition
Language identification
Speaker recognition / Speech synthesis
Forensic analysis of disputed utterances
Speaker identification by earwitness
Text Mining and Natural Language Processing
Relationship extraction
Topic segmentation and recognition
Natural language generation / understanding
Question answering
Sentiment analysis
Aspect based analysis in Social Media
Social network modelling and issues
Cloud computing for MSN
Trust and reputation modelling
Security and privacy in MSN
Intelligent Security Systems
Correlation of events posing security threats
Deep packet analysis
Network and system behaviour analysis
User behaviour modelling and analysis
Social media analysis for security
Smart and Intelligent Systems
Smart Transportation
Intelligent V2V and V2I Communication
Deep Learning for smart systems
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Proceedings:
All accepted papers will appear in the conference proceedings published by Springer series
Review Criteria:
Each submission must be identified as theoretical/methodological research, applied research, or
deployed application paper and will be reviewed using criteria appropriate to its category. The
criteria are as follows:
Paper Category: Theoretical/Methodological research paper
Review Criteria: Scientific significance; originality; technical quality; and clarity
Paper Category: Applied research paper
Review Criteria: Significance for scientific research or innovative commercial deployment;
originality; technical quality; and clarity
Paper Category: Deployed application paper
Review Criteria: Demonstrated practical, social, environmental or economic significance;
originality; treatment of issues of engineering, management & user acceptance; and clarity.
Submission Procedure:
Papers must be submitted online through EasyChair following the submission link:
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EasyChair Submission Link: https://www.easychair.org/conferences/?conf=mike2017
Springer publishes MIKE 2017 Proceedings in Lecture Notes in Artificial Intelligence (LNAI)
series (Approval Pending)
Authors should note that the papers should be of maximum 10 A4 pages (including figures and
tables) and manuscripts must be prepared with LaTex2e (llncs2e.zip). Author names and
affiliations details should be anonymised during the manuscript preparation so as to enable the
peer-review.
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DOUBLE-BLIND REVIEW:
MIKE 2017 uses a double-blind review process for paper selection.
Authors should not know the names of the reviewers of their papers, and reviewers should not
know the name(s) of the authors.
Please prepare your paper in a way that preserves anonymity of the authors.
Do not put your name(s) under the title.
Avoid using phrases such as “our previous work” when referring to earlier publications by the
authors.
Remove information that may identify the authors in the acknowledgements (e.g., co-workers
and grant IDs).
Check supplemental material (e.g., titles in the video clips, or supplementary documents) for
information that may identify the authors identity.
Avoid providing links to web sites that identify the authors.
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Submission Format:
Papers MUST be submitted in Springer LNCS format, which is the format required for the final
camera ready copy. We will accept:
Long papers: with a maximum of 10 pages Short papers: with a maximum of 6 pages
EXTRA PAGES: Authors may include 4 additional pages at an extra fee of $10 USD per page. In
exceptional cases, author’s request may be considered for the waiver of this fee based on the
merits of their paper.
Both long and short papers will be considered for poster and oral (short or long) presentation at
the conference based on the reviewing criteria above. Authors’ instructions along with LaTeX
(preferred) and Word macro files are available on the web at Springer’s Information for LNCS
Authors page (http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0). Authors of accepted
papers are required to transfer their copyrights to Springer. All submissions are required to be
in electronic format.