4 Nov
2022
4 Nov
'22
2:08 p.m.
日本データベース学会の皆様
（重複してお受け取りになった場合はご容赦ください）
同志社大学の桂井と申します。
来年5月25日〜28日に国際会議PAKDD2023が大阪で開催されます。
投稿締切は日本時間11月25日（金）17時です。
皆様からのご投稿、ご参加をお待ちしております。
===============================================================
[Call for Papers]
The 26th Pacific-Asia Conference on Knowledge Discovery and Data Mining
(PAKDD 2023)
http://pakdd2023.org/
Conference date: May 25-28, 2023 - Osaka, Japan (Onsite/online hybrid)
Paper Submission Deadline: Nov. 24, 2022
===============================================================
The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)
is one of the longest established and leading international conferences in
the areas of data mining and knowledge discovery. It provides an
international forum for researchers and industry practitioners to share
their new ideas, original research results, and practical development
experiences from all KDD related areas, including data mining, data
warehousing, machine learning, artificial intelligence, databases,
statistics, knowledge engineering, visualization, decision-making systems,
and the emerging applications.
The 26th edition of PAKDD will be held in Osaka, Japan, from May 25 to May
28, 2023.
The venue will be a hybrid of onsite and online.
[Topics]
PAKDD2023 welcomes high-quality, original, and previously unpublished
submissions in the theories, technologies, and applications on all aspects
of knowledge discovery and data mining. Topics of relevance for the
conference include, but not limited to the following.
Methods and algorithms:
Anomaly and outlier detection, Association rule, Classification,
Clustering, Data mining pipelines, Deep learning, Dimensionality detection
and feature selection, Ethics and fairness, Graphs and networks,
Interpretability and explainability, Kernel methods, Matrices and tensors,
Online and streaming algorithms, Parallel and distributed mining,
Probabilistic models and statistical inference, Regression, Reinforcement
learning, Relational learning, Security and privacy, Semi-supervised and
unsupervised learning, Theoretical foundations, Transfer learning and meta
learning, and Visualization and user interface.
Applications:
Big data, Computational Advertising, Financial data, Information retrieval
and search, Internet of Things, Intrusion and fraud detection, Medical and
biological data, Multimedia and multimodal data, Recommender systems,
Robotics, Scientific data, Social network analysis, Spatio-temporal data,
Texts, web, social media, and Time-series and streaming data.
[Paper Submission]
Paper submission must be in English. All papers will be double-blind
reviewed by the Program Committee based on technical quality, relevance to
data mining, originality, significance, and clarity. All paper submissions
will be handled electronically. Papers that do not comply with the
Submission Policy will be rejected without review.
Each submitted paper must include an abstract up to 200 words and be no
longer than 12 single-spaced pages with 10pt font size (including
references, appendices, etc.). Authors must use Springer LNCS/LNAI
manuscript submission guidelines for their submissions. All papers must be
submitted electronically through the CMT paper submission system in PDF
format only. Supplementary material may be submitted as a separate PDF
file, but reviewers are not obligated to consider this, and your manuscript
should, therefore, stand on its own merits without any supplementary
material. Supplementary material will not be published in the proceedings.
We require that any submission to PAKDD must not be already published or
under review at another archival conference or journal. Papers on arXiv do
not violate this rule as long as the submitted paper does not cite them.
Submitting a paper to the conference means that if the paper was accepted,
at least one author will complete the regular registration and attend the
conference to present the paper. For no-show authors, their papers will not
be included in the proceedings.
The conference will confer several awards, including Best Paper Award, Best
Student Paper Award, and Best Application Paper Award from the submissions.
Springer will publish the proceedings of the conference as a volume of the
LNAI series.
[Double-Blind Review]
Paper submission must adhere to the double-blind review policy. Submissions
must remove all details identifying the author(s) from the original
manuscript (including the supplementary files, if any), and the author(s)
should refer to their prior work in the third person and include all
relevant citations.
Because of the double-blind review process, non-anonymous papers that have
been issued as technical reports or similar cannot be considered for
PAKDD2023. An exception to this rule applies to manuscripts that were
published in arXiv not later than October 24, 2022, i.e., at least a month
before PAKDD’s submission deadline.
The author list and order cannot be changed after the paper is submitted.
[Formatting Template]
Formatting Template:
https://www.springer.com/gp/computer-science/lncs/conference-proceedings-gu…
.
All the Manuscripts must be prepared and submitted in accordance with the
above format. Usage of other formats may lead to disqualification of paper
for the conference.
[Submission Site]
https://cmt3.research.microsoft.com/PAKDD2023
[Important Dates]
Paper Submission Deadline: November 24, 2022
Paper Acceptance Notification: January 24, 2023
Camera Ready Papers Due: February 24, 2023
*All deadlines are 23:59 Pacific Standard Time (PST)
[Contact Information]
Program Co-Chairs of PAKDD2023
Hisashi Kashima, Wen-Chih Peng, Tsuyoshi Ide
pakdd2023(a)gmail.com
--
*************************************
Marie Katsurai, PhD
Associate Professor
Department of Intelligent Information Engineering and Sciences
Doshisha University
E-mail: katsurai(a)mm.doshisha.ac.jp
Website: https://mm.doshisha.ac.jp/