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NICDL 2018 : Nature-Inspired Computation in Data Mining and Machine Learning

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Link: https://easychair.org/conferences/?conf=nicdl2018
 
When Sep 15, 2018 - Oct 15, 2018
Where Call for Book Chapters
Abstract Registration Due Jun 15, 2018
Submission Deadline Jul 25, 2018
Notification Due Aug 20, 2018
Final Version Due Sep 15, 2018
Categories    optimization   nature-inspired algorithms   data mining   machine learning
 

Call For Papers

Nature-Inspired Computation in Data Mining and Machine Learning (NICDL2018)
"Call for Book Chapters"

[Due to many requests, the deadline has been extended. It is still possible
to submit your full book chapters by 10 Oct 2018.]

Nature-inspired computation, data mining and machine learning are three hot research areas in recent years. An edited book with the above title will be published by Springer in early 2019 to summarize the latest developments in these three areas with the emphasis on new techniques and applications as well as multidisciplinary interactions of these areas. We have already received 15 book chapters. Due to the diversity of the three areas covered in this book, we wish to invite more chapters to cover a more diverse range of topics.

Therefore, potential authors working in these areas are invited to contribute a book chapter in the following areas (but not limited to):
* Nature-inspired computation (NIC)
* Data mining (DM) techniques and applications
* Machine learning (ML) techniques and applications
* Big data and applications
* Artificial intelligence
* Swarm intelligence
* Evolutionary algorithms and metaheuristics
* Optimization methods and applications
* New methods and/or applications concerning NIC, DM and ML
* Other relevant algorithms and applications

Submissions are welcome via the EasyChair online submission system at
https://easychair.org/conferences/?conf=nicdl2018

Key dates:
Full chapter submission: 10 Oct 2018
Acceptance Notice: 20 Oct 2018
Final version: 31 Oct 2018

Chief Editor:
Prof. Xin-She Yang, Middlesex University, UK
email: x.yang ( at ) mdx.ac.uk

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