[dbjapan] Last CFP〆切1週間前：IEEE Bigdata Human-in-the-loop workshop 12月シアトルです ．

[Atsuyuki Morishima <mori [at] slis.tsukuba.ac.jp>]

dbjapanの皆様

筑波大の森嶋です．締め切り1週間前ですのでLast CFPをお送りします．
データxヒューマンファクターに関連する論文は幅広くカバーして
おります．Keynoteも超大物です．DBLP 掲載されます．

Project-in-progressは3ページなのでまだ間に合います．
Practitioner Paperも歓迎いたします．

是非とも投稿をご検討いただければ幸いです．
よろしく御願い申し上げます．

森嶋厚行

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The Second IEEE Workshop on
Human-in-the-loop Methods and Human-Machine Collaboration
in Big Data (IEEE HMData 2018) co-located with IEEE Bigdata 2018
Seattle, Dec. 10th (Tentative)
https://humanmachinedata.org
======================================
Overview

Human power is a key factor to maximize the impact of bigdata
technologies. This workshop addresses human-in-the-loop
approaches in bigdata lifecycle - in collecting, processing, analyzing,
utilizing, archiving and disposing them. The purpose of this workshop
is to give excellent opportunities for students, researchers and
practitioners to identify important research problems and exchange
their ideas on human-in-the-loop in the bigdata context. To make
the workshop an attractive place for those people, we solicit
practitioner papers as well as research papers, in order to facilitate
discussion among researchers who know solutions and practitioners
who know problems. We also would like to make the place valuable
for young researchers. All papers accepted for the workshop will be
included in the Workshop Proceedings published by the IEEE
Computer Society Press, made available at the Conference.
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Topics

This workshop covers a wide range of human-related topics in the
bigdata context, such as crowdsourcing, collaborative recommendation,
crowdsensing, workflow model for humans and machines, incentives,
human-assisted bigdata analysis, bigdata-human interaction,
supporting tools for humans in human-in-the-loop systems, security
and privacy in human-machine collaboration , human factors and
ELSI (ethical, legal and social issues) in human-in-the-loop systems,
and human-machine collaboration in real-world problems.
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Keynote

Professor Dan Weld (University of Washington)

Bio: Daniel S. Weld is Thomas J. Cable / WRF Professor in the Paul
G. Allen School of Computer Science & Engineering and Entrepreneurial
Faculty Fellow at the University of Washington. After formative education
at Phillips Academy, he received bachelor's degrees in both Computer
Science and Biochemistry at Yale University in 1982. He landed a Ph.D.
from the MIT Artificial Intelligence Lab in 1988, received a Presidential
Young Investigator's award in 1989, an Office of Naval Research Young
Investigator's award in 1990, was named AAAI Fellow in 1999 and
deemed ACM Fellow in 2005. Dan was a founding editor for the Journal
of AI Research, was area editor for the Journal of the ACM, guest editor
for Computational Intelligence and Artificial Intelligence, and was
Program Chair for AAAI-96. Dan has published two books and scads of
technical papers. Dan is an active entrepreneur with several patents
and technology licenses. He co-founded Netbot Incorporated, creator of
Jango Shopping Search (acquired by Excite), AdRelevance, a monitoring
service for internet advertising (acquired by Nielsen NetRatings), and
data integration company Nimble Technology (acquired by Actuate).
Dan is a Venture Partner at the Madrona Venture Group and on the
Scientific Advisory Boards of the Allen Institute for Artificial Intelligence
and the Madrona Venture Group. Dan teaches many courses, including
graduate classes on Artificial Intelligence, Extracting, Managing &
Personalizing Web Information and Intelligent User Interfaces, and
undergraduate classes on Artficial Intelligence, Advanced Internet
Systems, and Machine Learning. In 2012, Dan co-organized a workshop
on Crowdsourcing Personalized Online Education. During sabbaticals
Dan was a visiting professor at Griffith University in Brisbane, Australia
and visited the VIBE group at Microsoft Research.
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Important Dates

Oct 10, 2018: Due date for workshop papers submission (all categories)
Nov 1, 2018: Notification of paper acceptance to authors
Nov 15, 2018: Camera-ready of accepted papers
Dec 10-13, 2018: Workshops
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Submission

All submissions must be submitted electorically through CyberChair
(to be open soon). Please prefix your submission category such as
[Research Paper] to the Title of Paper field in the submission page.
For example, if you would like to submit a project-in-progress paper
"Crowd-centric Approach to Digital Archive Maintenance," you have
to put "[project-in-progress paper] Crowd-centric Approach to Digital
Archive Maintenance" into the Title of Paper field.

All papers accepted for the workshop will be included in the Workshop
Proceedings published by the IEEE Computer Society Press, made
available at the Conference.
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Submission Categories

Research Papers (*) (long presentation): They report significant and
original results relevant to the scope of this workshop. We solicit
innovative or thought-provoking work but they do not necessarily
have to reach the level of completion. The expected length is between
4 and 6 pages. The maximum length is 10 pages, though the paper
should be commensurate with the size of the contribution.

Practitioner papers (*)(long presentation): They present interesting
problems that require human-in-the-loop solutions in a variety of
application domains, or present the interesting results of applying
existing human-in-the-loop solutions to their domains. The expected
length is between 4 and 6 pages. The maximum length is 10 pages,
though the paper should be commensurate with the size of the contribution.

Project-in-progress papers: They present the goals,
challenges, and preliminary results of research or real-world projects
in progress. The maximum length is 3 pages.

(*) Some of the papers submitted to the research or practitioner paper
categories may be accepted as project-in-progress papers and allotted
to short presentation slots.

Format:
Papers should be formatted to IEEE Computer Society Proceedings
Manuscript Formatting Guidelines in the IEEE Bigdata 2018 CFP page
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Organization

Chairs
Senjuti Basu Roy (NJIT)
Lei Chen (HKUST)
Atsuyuki Morihsima (Univesity of Tsukuba)

Program Committee (to be extended)
Sihem Amer-Yahia (CNRS/LIG)
Yukino Baba (University of Tsukuba)
Wolf-Tilo Balke (Technische Universitat Braunschweig)
Adam Bradley (Amazon)
Marina Danilevsky (IBM Research Almaden )
Yoshiharu Ishikawa (Nagoya University)
Vana Kalogeraki (Athens University of Economics and Business)
Dongwon Lee (Penn State University)
John O\'Donovan (Univerisity of California Santa Barbara)
Satoshi Oyama (Hokkaido University)
Nobuyoshi Shimizu (Yahoo!Japan Research)
Siddharth Suri (Microsoft Research)
Yu Suzuki (NAIST)
Keishi Tajima (Kyoto University)
Saravanan Thirumuruganathan (QCRI)
Vladimir Zadorozhny (University of Pittsburgh)
Demetris Zeinalipour (Max Planck Institute for Informatics and
University of Cyprus)
Jing Zhang (Nanjing U. of Science ＆ Technology)
Yudian Zheng (Twitter)
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森嶋厚行

-- 
Atsuyuki Morishima <morishima-office [at] ml.cc.tsukuba.ac.jp>
Faculty of Library, Information and Media Science
Center for Artificial Intelligence Research, University of Tsukuba
JST CREST CyborgCrowd Project
http://crowd4u.org/ja/projects/crest-cyborgcrowd
The Crowd4U Initiative
http://crowd4u.org