[jsai-fin 0174] CFP: Deadline Extended to June, 8th: IEEE DSAA 2017 in Tokyo
Kiyoshi Izumi
izumi ＠ sys.t.u-tokyo.ac.jp
2017年 5月 30日 (火) 07:29:30 JST
SIG-FIN研究会の皆様 ←和泉
お世話になっています。
10月に品川で開催されるデータサイエンスの国際会議DSAAの
論文投稿〆切が6月8日まで延長されました。
金融データマイニングやテキストマイニングも対象となって
いますので、ぜひ投稿いただけましたら幸いです。
よろしくお願いいたします。
---------- Forwarded message ---------
2017年10月19～21日に東京品川にて開催されるIEEE国際会議DSAA2017の論文投稿
締め切りを6月8日（木）まで延長致しました．
Research track, Applications track, Special Session のカテゴリがあり，いずれの
締め切りも同じ日となります．論文フォーマットも共通です．
http://www.dslab.it.aoyama.ac.jp/dsaa2017/cfsspapers/
皆様のご投稿とご参加をお待ちしております．
----------------------------------------------------------
Apologize if this circulation interrupts you.
Due to many requests, the submission deadline to DSAA 2017 in Tokyo
(Research/Applications track and Special Sessions) has been extended to
June 8th:
http://www.dslab.it.aoyama.ac.jp/dsaa2017/cfsspapers/
======================================================
CALL For PAPERS
IEEE DSAA'2017: 2017 International Conference on
Data Science and Advanced Analytics
Tokyo, Japan
October 19-21, 2017
http://www.dslab.it.aoyama.ac.jp/dsaa2017/
======================================================
HIGHLIGHTS OF DSAA
* A very competitive acceptance rate (about 10%) for regular papers
* Jointly supported by IEEE, ACM and American Statistical Association
* Strong inter-disciplinary and cross-domain culture
* Strong engagement of analytics, statistics and industry/government
* Double blind, and 10 pages in IEEE 2-column format
INTRODUCTION
Data-driven scientific discovery is regarded as the fourth science
paradigm. Data science is a core driver of the next-generation science,
technologies and applications, and is driving new researches, innovation,
profession, economy and education across disciplines and across domains.
There are many associated scientific challenges, ranging from data capture,
creation, storage, search, sharing, modeling, analysis, and visualization.
Among the complex aspects to be addressed we mention here the integration
across heterogeneous, interdependent complex data resources for
real-time decision making, streaming data, collaboration, and
ultimately value co-creation. Data science encompasses the areas of
data analytics, machine learning, statistics, optimization and
managing big data, and has become essential to glean understanding
from large data sets and convert data into actionable intelligence, be
it data available to enterprises, society, Government or on the Web.
DSAA takes a strong interdisciplinary approach, features by its strong
engagement with statistics and business, in addition to core areas
including analytics, learning, computing and informatics. DSAA fosters
its unique Trends and Controversies session, Invited Industry Talks
session, Panel discussion, and four keynote speeches from statistics,
business, and data science. DSAA main tracks maintain a very competitive
acceptance rate (about 10%) for regular papers.
Following the preceeding three editions DSAA'2016 (Montreal),
DSAA'2015 (Paris), and DSAA'2014 (Shanghai), the 2017 IEEE International
Conference on Data Science and Advanced Analytics (DSAA'2017) aims to
provide a premier forum that brings together researchers, industry
practitioners, as well as potential users of big data, for discussion
and exchange of ideas on the latest theoretical developments in Data
Science as well as on the best practices for a wide range of
applications.
DSAA is also technically sponsored by ACM through SIGKDD and by the
American Statistical Association.
DSAA solicits then both theoretical and practical works on data science
and advanced analytics. DSAA'2017 will consist of two main tracks: Research
and Applications, and a series of Special sessions. The Research Track is
aimed at collecting original (unpublished nor under consideration at any
other
venue) and significant contributions related to foundations of Data Science
and Analytics. The Applications Track is aimed at collecting original papers
describing better and reproduciable practices with substantial contributions
to Data Science and Analytics in real life scenarios. DSAA special sessions
substantially upgrade traditional workshops to encourage emerging topics in
data science while maintain regirous selection criteria. Call for proposals
to
organize special sessions are highly encouraged.
IMPORTANT DATES:
Paper Submission deadline:
June 8, 2017 (extended)
Notification of acceptance:
July 25, 2017
Final Camera-ready papers due: August 15, 2017
Early Registration dealine: August 31, 2017
PUBLICATIONS:
All accepted papers, including main tracks and special sessions, will be
published by IEEE and will be submitted for inclusion in the IEEE Xplore
Digital Library. The conference proceedings will be submitted for EI
indexing
through INSPEC by IEEE. Top quality papers accepted and presented at the
conference will be selected for extension and invited to the special issues
of International Journal of Data Science and Analytics (JDSA, Springer).
TOPICS OF INTEREST -- RESEARCH TRACK
General areas of interest to DSAA'2017 include but are not limited to:
1. Foundations
Mathematical, probabilistic and statistical models and theories
Machine learning theories, models and systems
Knowledge discovery theories, models and systems
Manifold and metric learning
Deep learning and deep analytics
Scalable analysis and learning
Non-IID learning
Heterogeneous data/information integration
Data pre-processing, sampling and reduction
Dimensionality reduction
Feature selection, transformation and construction
Large scale optimization
High performance computing for data analytics
Architecture, management and process for data science
2. Data analytics, machine learning and knowledge discovery
Learning for streaming data
Learning for structured and relational data
Latent semantics and insight learning
Mining multi-source and mixed-source information
Mixed-type and structure data analytics
Cross-media data analytics
Big data visualization, modeling and analytics
Multimedia/stream/text/visual analytics
Relation, coupling, link and graph mining
Personalization analytics and learning
Web/online/social/network mining and learning
Structure/group/community/network mining
Cloud computing and service data analysis
3. Management, storage, retrieval and search
Cloud architectures and cloud computing
Data warehouses and large-scale databases
Memory, disk and cloud-based storage and analytics
Distributed computing and parallel processing
High performance computing and processing
Information and knowledge retrieval, and semantic search
Web/social/databases query and search
Personalized search and recommendation
Human-machine interaction and interfaces
Crowdsourcing and collective intelligence
4. Social issues
Data science meets social science
Security, trust and risk in big data
Data integrity, matching and sharing
Privacy and protection standards and policies
Privacy preserving big data access/analytics
Social impact and social good
TOPICS OF INTEREST -- APLICATIONS TRACK
Papers in this track should motivate, describe and analyze the
reproduciable use
of Data science tools and/or techniques in practical applications as well as
illustrate their actual impact on business and/or society.
We seek contributions that address topics such as (but not limited to)
the following:
Best practices and lessons learned from both success and failure
Data-intensive organizations, business and economy
Quality assessment and interestingness metrics
Complexity, efficiency and scalability
Big data representation and visualization
Business intelligence, data-lakes, big-data technologies
Data science education and training practices and lessons
Large scale application case studies and domain-specific
applications, such as:
- Online/social/living/environment data analysis
- Mobile analytics for hand-held devices
- Anomaly/fraud/exception/change/drift/event/crisis analysis
- Large-scale recommender and search systems
- Data analytics applications in cognitive systems, planning and
decision support
- End-user analytics, data visualization, human-in-the-loop,
prescriptive analytics
- Business/government analytics, such as for financial services,
manufacturing, retail, utilities, telecom, national security,
cyber-security, e-governance, etc.
PAPER SUBMISSION
Submissions to the main conference, including Research Track,
Applications Track, and Special Sessions should be made through the IEEE
DSAA'2017 Submission Web site.
The paper length allowed is a maximum of ten (10) pages, in 2-column U.S.
letter
style using IEEE Conference template (see the IEEE Proceedings Author
Guidelines:
http://www.ieee.org/conferences_events/conferences/publishing/templates.html
).
To help ensure correct formatting, please use the style files for
U.S. letter size found at the link above as templates for your
submission, which include both LaTeX and Word.
All submissions will be blind reviewed by the Program Committee on the
basis of technical quality, relevance to conference topics of interest,
originality, significance, and clarity. Author names and affiliations
must not appear in the submissions, and bibliographic references must be
adjusted to preserve author anonymity.
OTHER CALLS
Call for tutorials: http://www.dslab.it.aoyama.ac.jp/dsaa2017/cftutorials/
Call for special sessions:
http://www.dslab.it.aoyama.ac.jp/dsaa2017/cfspecsessions/
Call for sponsorship: http://www.dslab.it.aoyama.ac.jp/dsaa2017/cfsponsors/
ORGANIZING COMMITTEE
General Chairs:
Hiroshi Motoda, Osaka University, Japan
Fosca Giannotti, Information Science and Technology Institute
of the
National Research Council at Pisa, Italy
Tomoyuki Higuchi, Institute of Statistical Mathematics, Japan
Program Chairs -- Research Track
Takashi Washio, Osaka University, Japan
Joao Gama, University of Porto, Portugal
Program Chairs -- Application Track
Ying Li, DataSpark Pte. Ltd., Singapore
Rajesh Parekh, Facebook, also with KDD2016 and The Hive, USA
Special Session Chairs
Huan Liu, Arizona State University, USA
Albert Bifet, Telecom ParisTech, France
Richard De Veaux, Williams College, USA
Trends & Controversies Chairs
Philip S. Yu, University of Illinois at Chicago, USA
Pau-Choo (Julia) Chung, National Cheng Kung University, Taiwan
Award Chair
Bamshad Mobasher, DePaul University, USA
NGDS (Next Generation Data Scientist) Award Chairs
Kenji Yamanishi, University of Tokyo, Japan
Xin Wang, University of Calgary, Canada
Travel Awards Chair
Zhexue Huang, Shenzhen University, China
Tutorial Chairs
Zhi-Hua Zhou, Nanjing University, China
Vincent Tseng, National Chiao Tung University, Taiwan
Panel Chairs
Geoff Webb, Monash University, Australia
Bart Goethals, University of Antwerp, Belgium
Invited Industry Talk Chairs
Yutaka Matsuo, University of Tokyo, Japan
Hang Li, Huawei Technologies, Hong Kong
Publicity Chairs
Tu Bao Ho, Japan Advanced Institute of Science &
Technology, Japan
Diane J. Cook, Washington State University
Marzena Kryszkiewicz, Warsaw University of Technology, Poland
Local Organizing Chairs
Satoshi Kurihara, University of Electro-Communications, Japan
Hiromitsu Hattori, Ritsumeikan University, Japan
Publication Chair
Toshihiro Kamishima, National Institute of Advanced Industrial
Science and Technology, Japan
Web Chair
Kozo Ohara, Aoyama Gakuin University, Japan
Sponsorship Chairs
Yoji Kiyota, NEXT Co., Ltd, Japan
Kiyoshi Izumi, University of Tokyo, Japan
Tadashi Yanagihara, KDDI Corp., KDDI R\&D Laboratory, Japan
Longbing Cao, University of Technology Sydney, Australia
Byeong Kang University of Tasmania, Australia
CONTACT INFORMATION
Hiroshi Motoda motoda ＠ ar.sanken.osaka-u.ac.jp
Satoshi Kurihara skurihara ＠ uec.ac.jp
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