日本データベース学会の皆様
兵庫県立大学の大島裕明です。
ACM SIGIR-AP 2024が12/9~12の日程で早稲田大学西早稲田キャンパスにて
開催されます。
質の高い研究発表が行われる国際会議です。
チュートリアルやワークショップについても充実しております。
ぜひ、多くの皆様にご参加いただければと思います。
よろしくお願いいたします。
======================================================================
ACM SIGIR-AP 2024@早稲田大学 参加募集案内
======================================================================
■会議名
The 2nd International ACM SIGIR Conference on Information Retrieval
in the Asia Pacific (ACM SIGIR-AP 2024)
■日時
2024年12月9日(月)~12日(木)
■場所
早稲田大学 西早稲田キャンパス 63号館
(〒169-8555 東京都新宿区大久保3-4-1)
■Webサイト
https://www.sigir-ap.org/sigir-ap-2024/
■参加登録(Regular:11月16日21:00まで,Late:12月2日21:00まで)
https://www.sigir-ap.org/sigir-ap-2024/registration/
======================================================================
■アジア太平洋地域における情報検索の国際会議
SIGIR-APはACMが開催する情報検索に関する国際会議です。情報検索の最高峰
の国際会議ACM SIGIRのアジア・太平洋版として、同地域における情報検索の
研究開発を促進し、広めることを目的としています。昨年、第1回となる
SIGIR-AP 2023が北京で開催され、今年の第2回のSIGIR-AP 2024が東京の早稲
田大学で開催されます。
■情報検索に関する質の高い研究発表
SIGIR-AP 2024では、情報検索に関連する質の高い論文から選ばれた31件の発
表が行われます。また、ACM Transactions on Information Systems (TOIS)
論文誌に採択された論文から、6件の発表が行われます。これらの発表は
12月10日~12日に行われます。
■魅力的なキーノート
12月10日にアジア経済研究所の牧野百恵先生から、12月11日に国立情報学
研究所所長の黒橋禎夫先生からキーノートを行っていただきます。
https://www.sigir-ap.org/sigir-ap-2024/keynote-speaker/
◎Information Experiment: What Does Empirical Microeconomics Tell Us?
Speaker: Momoe Makino, The Institute of Developing Economies,
Japan External Trade Organization, Japan
12月10日のキーノートはアジア経済研究所の牧野百恵先生にお話しいただきます。
牧野先生は開発ミクロ経済学の実証研究を専門とされており、その一環で、
『ジェンダー格差 -
実証経済学は何を語るか』という著書も執筆されています。本キーノートでは、因果関係と相関関係の区別などに言及しながら、実証研究におけるエビデンスについて論じ、「ランダム化比較試験」や「自然実験」などを含む因果推論にまつわる手法の紹介や、それらを用いた実際の実証研究における知見についてご紹介いただく予定です。
参考:https://www.ide.go.jp/Japanese/Researchers/makino_momoe.html
参考:https://www.chuko.co.jp/ebook/2023/08/518558.html
◎From Data Platforms to Knowledge Infrastructure
Speaker: Sadao Kurohashi, National Institute of Informatics, Japan
12月11日のキーノートは国立情報学研究所所長の黒橋禎夫先生にお話しいただ
きます。「オープンサイエンス」を支える基盤として、国立情報学研究所(NII)
で開発・運用しておられるNII研究データ基盤のご紹介や、そのような基盤を
利用し、あらゆる研究分野における論文、データ、計算リソースを包括的に含
む環境が構築され、研究データエコシステムが知識インフラとしてある社会に
ついて論じていただく予定です。また、NIIが中心となって開発を続けている
LLM勉強会(llm-jp)による大規模言語モデル(LLM)開発の状況についてもご
紹介いただく予定です。
参考:https://www.nii.ac.jp/faculty/director/
参考:https://llm-jp.nii.ac.jp/
■最新の研究動向を知ることができるチュートリアル
初日の12月9日には、5件のチュートリアルが開催されます。
https://www.sigir-ap.org/sigir-ap-2024/tutorial/
<Full-day>
◎Evaluating Cognitive Biases in Conversational and Generative IIR:
A Tutorial
Speakers: Leif Azzopardi and Jiqun Liu
<Half-day>
◎Query Performance Prediction: Techniques and Applications
in Modern Information Retrieval
Speakers: Negar Arabzadeh, Chuan Meng, Mohammad Aliannejadi and
Ebrahim Bagheri
◎Retrieval-Enhanced Machine Learning: Synthesis and Opportunities
Speakers: Fernando Diaz, Andrew Drozdov, To Eun Kim,
Alireza Salemi and Hamed Zamani
◎Paradigm Shifts in Team Recommendation: From Historical
Subgraph Optimization to Emerging Graph Neural Network
Speakers: Mahdis Saeedi, Christine Wong and Hossein Fani
◎Neural Lexical Search with Learned Sparse Retrieval
Speakers: Andrew Yates, Carlos Lassance, Sean MacAvaney,
Thong Nguyen and Yibin Lei
■議論ワークショップ
最終日の12月12日の午後には、3件のワークショップが開催されます。
https://www.sigir-ap.org/sigir-ap-2024/program-workshops/
◎R3AG: First Workshop on Refined and Reliable Retrieval
Augmented Generation
Organizers: Zihan Wang, Xuri Ge, Joemon Jose, Haitao Yu, Weizhi Ma,
Zhaochun Ren and Xin Xin
URL: https://r3ag-sigir-ap.github.io/
◎The First Workshop on Evaluation Methodologies,
Testbeds and Community for Information Access Research (EMTCIR 2024)
Organizers: Makoto P. Kato, Noriko Kando, Charles Clarke and Yiqun Liu
URL: https://emtcir2024.github.io/
◎The 1st Workshop on User Modelling
in Conversational Information Retrieval (UM-CIR)
Organizers: Praveen Acharya, Gareth J.F Jones, Xiao Fu, Aldo Lipani,
Fabio Crestani and Noriko Kando
URL: https://um-cir.github.io/
■フレキシブルな参加形態
SIGIR-AP 2024では、早稲田大学西早稲田キャンパスにおけるオンサイト参加
に加えて、オンライン参加も可能なハイブリッド開催となっています。オン
ライン参加の参加費はオフライン参加に比べて抑えられていますので、東京
への出張が困難な場合でも参加のご検討をいただければと思います。また、
学生や、ACMメンバーには、参加費の割引があります。ワークショップのみの
参加申込も可能です。皆様、ぜひ、Regular申込期限の11月16日21:00までに、
参加登録をしていただければと思います。
■サステナブルな会議を目指して
SIGIR-APは、サステナブルな会議の実現を目指しています。ハイブリッド開
催であることもその一環です。CO2排出量の削減、食品廃棄物の削減、その他
あらゆる種類の廃棄物の削減を念頭に会議の運営を行っています。
■運営委員
◎General Chairs
Tetsuya Sakai, Waseda University, Japan
Emi Ishita, Kyushu University, Japan
Hiroaki Ohshima, University of Hyogo, Japan
◎PC Chairs
Faegheh Hasibi, Radboud University, Netherlands
Jiaxin Mao, Renmin University of China, China
Joemon Jose, University of Glasgow, United Kingdom
◎Tutorial / Workshop Chairs
Masaharu Yoshioka, Hokkaido University, Japan
Kazunari Sugiyama, Osaka Seikei University, Japan
◎Finance Chair
Kazutoshi Umemoto, The University of Tokyo, Japan
◎Local Arrangement Chairs
Makoto Kato, University of Tsukuba, Japan
Hidetsugu Nanba, Chuo University, Japan
◎Satellite Chair
Oleg Zendel, RMIT University, Australia
◎Local Arrangement
Sijie Tao, Waseda University, Japan
Yuhang Dong, Waseda University, Japan
Mingming Liu, Waseda University, Japan
Haodong Liu, Waseda University, Japan
◎Student Gathering Chair
Shota Hachisuka, Chuo University, Japan
◎Proceedings Chair
Atsushi Keyaki, Hitotsubashi University, Japan
◎Sponsorship Chairs
Qingyao Ai, Tsinghua University, China
Yuya Matsumura, LayerX Inc., Japan
◎Registration / Visa Chairs
Kosetsu Tsukuda, AIST, Japan
Masako Nomoto, RIKEN, Japan
◎Web Chairs
Haitao Yu, University of Tsukuba, Japan
Yumo Yao, University of Tsukuba, Japan
◎Publicity Chairs
Noriko Kando, National Institute of Informatics, Japan
Takehiro Yamamoto, University of Hyogo, Japan
Charles Clarke, University of Waterloo, Canada
Prasenjit Majumder, DAIICT, India
◎Best Paper Chairs
Mark Sanderson, RMIT University, Australia
Bhaskar Mitra, Microsoft Research, United Kingdom
Negin Rahimi, University of Massachusetts Amherst, USA
--
Hiroaki Ohshima, Associate Professor
Graduate School of Information Science,
University of Hyogo
8-2-1 Gakuen-nishimachi
Nishi-ku, Kobe, Hyogo 651-2197, Japan
Email: ohshima(a)ai.u-hyogo.ac.jp
Tel: +81-78-794-5349
日本データベース学会の皆様(複数お受け取りの際にはご容赦ください)
お茶の水女子大学の伊藤貴之と申します。
計算機可視化に特化した国際会議では3番めの規模を有する
IEEE PacificVis 2025 が4月22日〜25日に台北で開催されます。
伊藤は昨年度に引き続き Conference Track の論文委員長を務めています。
だいぶ締切が迫っていますが、11月13日アブストラクト入力期限、
11月20日原稿提出期限で論文を募集しております。
日本からもたくさんの投稿を期待しています。なにとぞよろしくお願いいたします。
論文の書式についてはこちらに詳細が掲載されています。
https://pacificvis2025.github.io/pages/Common-call-for-papers.html
IEEE PacificVis 2025 solicits novel research contributions and innovative applications in all areas of visualization. PacificVis is a unified visualization conference covering topics including visualization techniques and systems, interactions, analytics and decision support, theoretical contributions to visualization, empirical studies, and visualization applications in domains such as (but not limited to) biological sciences, education, machine learning, physical sciences, security, and social science.
IEEE PacificVis 2025 will be held in Taipei, Taiwan on April 22?25, 2025. The conference accepts a range of scientific contributions ranging from full research papers, short papers, and posters. This year, PacificVis has a TVCG journal paper track, a conference full paper track, and a short paper (VisNotes) track with consecutive deadlines.
Conference Trackの詳細説明はこちらに掲載されています。
https://pacificvis2025.github.io/pages/Conference-papers.html
Submissions are invited to the new conference paper track at IEEE PacificVis 2025. Papers demonstrating high quality in terms of originality, rigor, and significance will be published in the IEEE PacificVis conference proceedings. Both new submissions and papers rejected from the TVCG journal track are invited to be submitted to the conference paper track, with optional reviewer continuity.
The rejected papers from the TVCG journal track are not automatically forwarded to the conference paper track. However, the deadlines for the TVCG and conference paper tracks are explicitly organized so that a paper rejected for the TVCG journal paper track can optionally be revised and resubmitted to the conference paper track. We encourage authors of rejected papers to take advantage of this mechanism.
Following the initial notification of review results, conditionally accepted papers (including supplemental material) will undergo a revision and review cycle in order to ensure that they are acceptable for publication and presentation in the conference proceedings. The paper and its supplemental material will also be archived in the IEEE Digital Library, in accordance with its standard terms and conditions.
The conference track of PacificVis 2025 will especially invite education and system papers. The education papers are supposed to contribute to the education of visualization experts and to the education of general users to improve their visualization literacy, and will be reviewed with emphasis on the uniqueness and effectiveness of educational methods rather than on technical novelty. The system papers are supposed to contribute to the development of visualization systems, and papers will be reviewed with emphasis on the completeness and practicality of the system rather than on theoretical novelty. For both sessions, please specify the session to which you wish to submit your paper by clicking the check box provided on the submission form.
Conference track - Abstracts November 13, 2024
Conference track - Papers November 20, 2024
Conference track - Notification (1st round) December 20, 2024
Conference track - Revisions (2nd round) January 13, 2025
Conference track - Final notification (2nd round) January 27, 2025
Conference track - Camera-ready papers February 10, 2025
Original, unpublished full papers of up to 9 + 2 pages (with only acknowledgments and references on the last two pages) are invited.
Paper Chairs
Takayuki Itoh Ochanomizu University
Filip Sadlo Heidelberg University
Yu-Shuen Wang National Yang Ming Chiao Tung University
Takayuki Itoh (伊藤貴之) (itot(a)is.ocha.ac.jp)
Dept. of Humanity Data Engineering / Dept. of Information Sciences,
Director of Center for AI and Data Science, Ochanomizu University
http://itolab.is.ocha.ac.jp/~itot/
DBJapanのみなさま
行動と振る舞いコンピューティングに関する国際会議ABC2025のCall For Papersです。
アブダビのグランドモスクと、学会会場の写真を添付します。
・11月タイトル、12月論文締め切りなので、ぜひ、投稿しませんか?
・今後の更新情報を知りたい方は
abc2025(a)autocare.ai
まで空メールをください。
(ぜひ、周知をお願いいたします。)
井上創造
[image: PXL_20241016_154008821.jpg]
---------- CALL FOR PAPERS -----------
The 7th International Conference on Activity and Behavior Computing
(IEEE Technically Co-sponsored)
Apr. 21-25 , 2025, Khalifa University, Abu Dhabi, UAE (Hybrid)
https://abc-research.github.io/
(Please send an empty email to abc2025(a)autocare.ai to get updates!)
Human Activity Recognition has been researched in thousands of papers so
far, with mobile / environmental sensors in ubiquitous / pervasive domains,
and with cameras in vision domains. As well, Human Behavior Analysis is
also explored for long-term health care, rehabilitation, emotion
recognition, human interaction, and so on. However, many research
challenges remain for realistic settings, such as complex and ambiguous
activities / behavior, optimal sensor combinations, (deep) machine
learning, data collection, platform systems, and killer applications.
In this conference, we comprehend such research domains as ABC: Activity
and Behavior Computing, and provide an open and a confluent place for
discussing various aspects and the future of the ABC.
CALL FOR PAPERS
We welcome 3 categories of papers: regular papers, position papers, and
challenge papers. The submitted papers are peer reviewed by expert
researchers, and accepted based on the research quality.
Accepted and presented papers will be published as IEEE Proceedings or a
J-Stage open access journal.
SCOPE
• Mobile sensor-based ABC
• Environmental sensor-based ABC
• Vision-based ABC
• Multimodal ABC
• Physical / semantic analysis of ABC
• Gait analysis
• Sleep analysis
• Emotion recognition / analysis
• ABC with deep learning
• ABC data mining
• Data collection
• ABC systems
• Interactive ABC
• Healthcare applications
• Nursing applications
• Elderly care applications
• Sports applications
• Business applications
• Tools for industry
• ABC in the wild
CATEGORIES
- Regular papers (4-10 pages) : full technical content papers, published in
+ IEEE proceedings or
+ J-Stage open access journal.
- Position papers (2-4 pages): describe the challenges and future
directions of ABC based on problems that arise when systems are deployed in
real settings (Not to be published).
- Challenge papers: we will provide a dataset and accept results for a
recognition challenge with papers describing the methods and the results.
IMPORTANT DATES
- Title and Abstract: Nov 11, 2024
- Paper deadline: Dec 9, 2024
- Review result: Jan 13, 2025
- Resubmission: Feb 10, 2025
- Camera ready: Mar 10, 2025
- Conference: Apr 21-25, 2025
COMMITTEE
GENERAL CHAIRS
- Kinda Khalaf, Khalifa University, UAE
- Fady Alnajjar, UAE University, UAE
- Sozo Inoue, Kyushu Institute of Technology, Japan
- Md Atiqur Rahman Ahad, University of East London, UK
PROGRAM CHAIRS
- Guillaume Lopez, Aoyama Gakuin University, Japan
- Tahera Hossain, Nagoya University, Japan
ADVISORY BOARD
- Anind Dey, University of Washington, USA
- Björn W. Schuller, Imperial College London, UK and Technical University
of Munich, Germany
- Jeffry Cohn, University of Pittsburgh, USA
- Kristof Van Laerhoven, University of Siegen, Germany
- Michael Beigl, Karlsruhe Institute of Technology, Germany
- Paul Lukowicz, RPTU / DFKI, Germany
- Thomas Plötz, Georgia Institute of Technology, USA
- Masahiko Inami, University of Tokyo, Japan
HISTORY
ABC2019 Spokane (USA)
ABC2020 Kitakyushu (Japan)
ABC2021 Bangkok (Online)
ABC2022 London (UK)
ABC2023 Kaiserslautern (Germany)
ABC2024 Nakatsu & Kitakyushu (Japan)
----------------------------------
---
Sozo Inoue
日本データベース学会の皆様、京都大学 首藤です。
国際会議 IEEE BigComp の論文募集、ワークショップ募集をご案内致します。
ビッグデータとスマートコンピューティングに関する国際会議で、
開催は来年 2月、場所はマレーシアのコタキナバルです。
投稿期限が 9/28(土) と迫っていますが、延びそうな気がします。
投稿を御検討頂けましたら幸いです。
IEEE BigComp 2025
https://www.bigcomputing.org/conf2025/
February 9 - 12, 2025
Kota Kinabalu, Malaysia
Big data and smart computing are emerging research fields that have
been drawing much attention from diverse disciplines including
computer science, information technology, and social sciences. The
goal of the International Conference on Big Data and Smart Computing
(BigComp), initiated by KIISE (Korean Institute of Information
Scientists and Engineers), is to provide an international forum for
exchanging ideas and information on current studies, challenges,
research results, system developments, and practical experiences in
these emerging fields among researchers, developers, and users from
academia, business and industry. Following the successes of the
previous BigComp conferences in Bangkok, Thailand (2014), Jeju, Korea
(2015), Hong Kong, China (2016), Jeju, Korea (2017), Shanghai, China
(2018), Kyoto, Japan (2019), Busan, Korea (2020), Jeju, Korea (2021),
Daegu, Korea (2022), Jeju, Korea (2023), and Bangkok, Thailand (2024),
the 2025 IEEE International Conference on Big Data and Smart Computing
(IEEE BigComp 2025) will be held in Kota Kinabalu, Malaysia. The
conference is co-sponsored by IEEE and KIISE. IEEE BigComp 2025
invites authors to submit original research papers and as well
original work-in-progress reports on big data and smart computing.
BigComp 2025 will be held in Kota Kinabalu, Malaysia. Kota Kinabalu is
the capital of Malaysia’s Sabah state in the northern part of the
island of Borneo. Often referred to as KK, it’s a coastal city partly
surrounded by rainforest. It's known for its bustling markets, modern
boardwalk, beaches and waterfront Kota Kinabalu City Mosque. It is
also a gateway to Kinabalu National Park, the home of 4,095m-high
Mount Kinabalu.
TOPICS of interest:
We invite the submission of original research contributions in the
following areas, but also welcome any original contributions that may
cross the boundaries among areas or point in other novel directions.
In addition, BigComp 2025 encourages submissions about products,
practices, and services in industry:
In particular, we strongly encourage big data and smart computing
specialists in industry to submit their papers as [Industrial track
papers].
• Big data analytics and social media
• Big data applications / big data as a service
• Big data ecosystem
• Bioinformatics, multimedia, smartphones, etc.
• Cloud and grid computing for big data
• Crowdsourcing and human-in-the-loop
• Data mining and data science
• Data and information quality
• Disaster analysis
• Infrastructure and platform for big data and smart computing
• Knowledge graph, graph data management and mining
• Machine learning and AI for big data
• Machine learning and AI theory and fundamentals
• Mobile communications and smart location-based services
• Recommender systems
• Search/retrieval and generation of big data
• Security and privacy for big data
• Smart computing models, tools, and devices
• Techniques, models and algorithms for big data
• Tools and systems for big data
• Understanding multi-modal data
• Big data in the era of LLMs
Journal Publication:
Accepted papers will be published in the conference proceedings to be
submitted to IEEE Xplore, and a set of selected papers will be invited
for possible publication to the following SCI(E) journal after further
revision and extension:
• Sensors
• Electronics
Submission
Original papers formatted in PDF according to the IEEE two-column
format for conference proceedings must be submitted through EasyChair
https://easychair.org/conferences/?conf=bigcomp2025. Regular papers
are limited to 8 pages and short ones to 4 pages. BigComp 2025 adopts
double-blind review policy. For details, please see the submission
guideline at the conference homepage.
The manuscripts submitted to the [Industrial track] will need add
“[Industrial paper]” in front of the paper title and will be reviewed
in a separate process for the [Industrial track papers].
Important Dates (Timezone: AoE)
• Paper submission: September 28, 2024
• Tutorial/Workshop proposal: September 28, 2024
• Notification of acceptance: November 23, 2024
• Camera-ready: December 14, 2024
• Early registration: January 25, 2025
• Conference dates: February 9~12, 2025
データベースな皆さま
# 重複して受け取られた場合はご容赦ください
筑波大学の吉田です,こんにちは。
計算社会科学会では,2024年12月にハイブリッド(現地はワシントンD.C.)で開催されるIEEE BigData
2024において,計算社会科学(Computational Social Science)に関するワークショップを企画しています。
このワークショップでは,大規模社会データ分析研究,社会シミュレーションによる理論的研究,バーチャルラボ(ウェブを使った大規模行動実験)による実験的研究,ソーシャルメディア分析などを使い,人間行動や社会現象を理解することを目指した研究論文を募集します。
論文はIEEE国際会議フォーマットで最大10ページを受け付け,採録された論文はIEEE Xploreに掲載される見込みです。
論文の締切は,当初より延長し,2024年10月15日です。多数のご投稿をお待ちしています。
https://css-japan.com/abcss2024/http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=182584
======================================
The 9th International Workshop on Application of Big Data for
Computational Social Science (ABCSS2024 @ IEEE BigData 2024)
(IEEE BigData 2024 Workshop)
https://css-japan.com/abcss2024/
======================================
Despite the progress of traditional social science, modern social
science is facing a serious paradigm shift due to the development of
computer and Internet technologies. Human behavior and social
phenomena is possible to be quantified by big data digitally tracing
online activities and mobility records at a granular level. In some
cases, big data can be analyzed using technologies evolving in the
natural sciences, such as physics, chemistry, and biology.
Experimental data and multiple results from theoretical and
computational simulations complement them. Both theoretically and
analytically grounded insights may open new doors of computational
social sciences. From this perspective, we hold a series of annual
workshops on application of big data for computational social science
for several years. The scope of the workshop includes, but is not
limited to, big data applications, big data collection and use, an
integrated framework for theory, simulation, statistics, and
experiments.
* DATE & PLACE
December 15-18, 2024. (Hybrid Conference / Washington DC, USA)
In conjunction with the 2024 IEEE International Conference on Big Data
(IEEE BigData 2024)
http://bigdataieee.org/BigData2024/
* RESEARCH TOPICS
- Application of Sociology/Sociophysics using Big Data
- Application of Econometric/Econophysics using Big Data
- Social Media Data analyses from economic/political/social perspective
- Informatics using social Big Data
- Marketing science using social Big Data
- Business analytics using Big Data on consumer behavior
- Culturomics and art management
- Analysis of reputation of entertainment using Big Data
* IMPORTANT DATES
- October 15, 2024 (Extended!!)
Workshop Papers submission
- November 4, 2024
Notification of Acceptance/Rejection
- November 20, 2024
Camera-ready Submission
* SUBMISSION
We accept papers of up to 10 pages (6 to 8 pages are recommended).
Submitted papers will undergo a peer review process, coordinated by
the Program Committee Members of our workshop.
https://bit.ly/abcss2024submission
Submitted papers should be formatted to the IEEE Conference
Proceedings format (see link to below).
https://www.ieee.org/conferences/publishing/templates.html
All registered papers that presented in this workshop will be
submitted to IEEE Xplore with main conference papers, and will be
submitted into some indexing system such as Web of Science, Scopus,
DBLP and others.
Main Chairs
- Fujio Toriumi, The University of Tokyo, Informatics
- Isamu Okada, Soka University, Informatics
- Hiroki Takikawa, The University of Tokyo, Sociology
- Mitsuo Yoshida, University of Tsukuba, Informatics
Drop us an email at abcss [at] css-japan.com if you have any questions.
--
Mitsuo Yoshida < mitsuo(a)gssm.otsuka.tsukuba.ac.jp >
Institute of Business Sciences,
University of Tsukuba
https://www.gssm.otsuka.tsukuba.ac.jp/~mitsuo/
MLの皆様
*重複して受け取られた場合はご容赦ください/Apologies for cross-posting*
北見工業大学のプタシンスキと申します.
現在,Information Processing&Management(IP&M)(IF:7.4)ジャーナルにて「Special Issue on Causal Reasoning in Language Models」(言語モデルにおける因果推論)という特集号のため論文募集を行っております.
原稿の提出締め切りは2025年3月31日ですが,論文は投稿後すぐに査読に送られ,採択された場合すぐに公開となります.
論文の投稿をどうぞご検討ください。
https://www.sciencedirect.com/journal/information-processing-and-management…
どうぞよろしくお願いいたします.
ミハウ・プタシンスキ(博士/情報科学,准教授)
テキスト情報処理研究室 北見工業大学
〒090-8507 北見市公園町165番地
TEL/FAX: 0157-26-9327
michal(a)mail.kitami-it.ac.jp
============================================
Journal: Information Processing & Management (Impact Factor: 7.4)
Special Issue on "Causal Reasoning in Language Models"
Guest Editors:
- Michal Ptaszynski (Kitami Institute of Technology), michal(a)mail.kitami-it.ac.jp
- Rafal Rzepka (Hokkaido University)
- Rafal Urbaniak (University of Ghent)
Introduction:
Causal reasoning is a fundamental cognitive ability that allows humans to understand the cause-and-effect relationships in the world around them. Integrating causal reasoning capabilities into language models has emerged as a promising research direction, with significant implications for natural language processing (NLP) and artificial intelligence (AI) applications. The special issue on "Causal Reasoning in Language Models" aims to provide a platform for researchers to explore the latest advancements and challenges in this burgeoning field.
Topics of Interest:
We invite submissions on a wide range of topics related to causal reasoning in language models, including but not limited to:
- Causal inference techniques in natural language processing
- Evaluating causal understanding in large language models
- Causal representations in transformer architectures
- Counterfactual reasoning capabilities of language models
- Causal discovery from unstructured text data
- Incorporating causal knowledge into language model pre-training
- Causal explanation generation using language models
- Bias and fairness in causal language modeling
- Causal reasoning for improved few-shot and zero-shot learning
- Temporal and event causal reasoning in language models
- Theoretical frameworks for representing causal knowledge in language models
- Methodologies for incorporating causal reasoning into NLP tasks, such as text generation, question answering, and summarization
- Evaluation metrics and benchmarks for assessing the performance of causal reasoning models in language understanding tasks
- Applications of causal reasoning in real-world scenarios, including healthcare, finance, social media analysis, and more
- Ethical considerations and societal implications of integrating causal reasoning into AI systems
- Interdisciplinary approaches that combine insights from linguistics, cognitive science, and computer science to advance causal reasoning in language models
Submission Guidelines:
Papers submitted to this special issue must adhere to the submission guidelines of Information Processing & Management. Manuscripts should be original, unpublished works not currently under review elsewhere. All submissions will undergo a rigorous peer review process to ensure high quality and relevance to the special issue.
Important Dates:
- Submission opens: 2024-7-31
- Submission closes: 2025-3-31
Submission Instructions:
Submit your manuscript to the Special Issue category (VSI: CAUSAL LLMs) through the online submission system of Information Processing & Management (https://www.editorialmanager.com/ipm/default.aspx). All the submissions should follow the general author guidelines of Information Processing & Management (https://www.sciencedirect.com/journal/information-processing-and-management). For any inquiries or further information, please contact the Managing Guest Editor at michal(a)mail.kitami-it.ac.jp.
Conclusion:
We encourage researchers from academia and industry to contribute their latest findings and innovations to this special issue. By bringing together a collection of high-quality papers on causal reasoning in language models, we aim to advance the state of the art in NLP, foster interdisciplinary collaborations, and pave the way for future developments in AI.
We look forward to your contributions.
Sincerely,
Michal Ptaszynski, in the name of all Guest Editors
============================================
日本データベース学会の皆様
早稲田大学の山名です。
JSTでは、以下の国際シンポジウムを開催いたしますので、お時間がございましたら
ご参加いただければ幸いです。
==
2024/9/12(木) 9:25-16:29@日本科学未来館(東京都江東区青海2-3-6)
「Society5.0を支える革新的コンピューティング技術」 国際シンポジウム
https://www.jst.go.jp/kisoken/crest/com-revol/index.html
配信もありますが、ポスター・デモを除きます。
==
本シンポジウムは、坂井先生@東大が領域長を務める
CREST「 「Society5.0を支える革新的コンピューティング技術」 のもと
採択されたCRESTプロジェクトの発表の他、
Intelligent Cyber-Physical Systems: Harnessing AI and ML Innovations for Social Good
Radu Marculescu (Professor, Texas University at Austin)
9:50-10:50
の基調講演があります。
講演者
テキサス大学オースティン校 Radu Marculescu 教授
講演者略歴:
ラドゥ・マルクレスク(Radu Marculescu)教授(IEEEフェロー・ACMフェロー)
テキサス大学オースティン校 電気・コンピュータ工学部 教授 兼 ローラ・ジェニングス・ターナー チェア。
2000年から2019年まで、カーネギーメロン大学 電気・コンピュータ工学部 教授。
現在は、コンピュータビジョン、バイオイメージング、ソーシャルセンシング、およびインターネット・オブ・シングス
(IoT)アプリケーションのためのシステム設計と最適化のためのML/AIアルゴリズムとツールの開発等の
研究を行う。2019年には、ネットワーク・オン・チップの設計、分析、および最適化の科学への重要な
貢献に対してIEEE Computer Society Edward J. McCluskey Technical Achievement Awardを
受賞。最近では、The International Conference on Hardware/Software Co-Design and
System Synthesis (CODES) で、2020年ESWEEK Test-of-Time Awardを受賞。
IEEEフローおよびACMフェロー。
==
早稲田大学 山名早人
日本データベース学会のみなさま
筑波大学の天笠です.お世話になっております.
知識グラフに関する国際会議 ICKG 2024 の論文募集をご案内しま
す.関連する成果をお持ちでご興味があれば,投稿をご検討くださ
い.よろしくお願いいたします.
天笠俊之
The 15th IEEE International Conference on Knowledge Graph (ICKG), December 11-12, Abu Dhabi, UAE
http://ickg2024.openkg.cn
All deadlines are at 11:59PM Pacific Daylight Time.
Paper submission (abstract and full paper): July 31, 2024 (!!!Extended to September 2nd, 2024!!!)
Notification of acceptance/rejection: September 30, 2024
Camera-ready deadline and copyright forms: October 15, 2024
Early Registration Deadline: November 11, 2024
Conference: December 11-12, 2024
The annual IEEE International Conference on Knowledge Graph (ICKG) provides a premier international forum for presentation of original research results in knowledge discovery and graph learning, discussion of opportunities and challenges, as well as exchange and dissemination of innovative, practical development experiences. The conference covers all aspects of knowledge discovery from data, with a strong focus on graph learning and knowledge graph, including algorithms, software, platforms. ICKG 2024 intends to draw researchers and application developers from a wide range of areas such as knowledge engineering, representation learning, big data analytics, statistics, machine learning, pattern recognition, data mining, knowledge visualization, high performance computing, and World Wide Web etc. By promoting novel, high quality research findings, and innovative solutions to address challenges in handling all aspects of learning from data with dependency relationship.All accepted
papers will be published in the conference proceedings by the IEEE Computer Society. Awards, including Best Paper, Best Paper Runner up, Best Student Paper, Best Student Paper Runner up, will be conferred at the conference, with a check and a certificate for each award. The conference also features a survey track to accept survey papers reviewing recent studies in all aspects of knowledge discovery and graph learning. At least five high quality papers will be invited for a special issue of the Knowledge and Information Systems Journal, in an expanded and revised form. In addition, at least eight quality papers will be invited for a special issue of Data Intelligence Journal in an expanded and revised form with at least 30% difference.
Topics of Interest
Topics of interest include, but are not limited to:
Foundations, algorithms, models, and theory of knowledge discovery and graph learning
Knowledge engineering with big data.
Machine learning, data mining, and statistical methods for data science and engineering.
Acquisition, representation and evolution of fragmented knowledge.
Fragmented knowledge modeling and online learning.
Knowledge graphs and knowledge maps.
Graph learning security, privacy, fairness, and trust.
Interpretation, rule, and relationship discovery in graph learning.
Geospatial and temporal knowledge discovery and graph learning.
Ontologies and reasoning.
Topology and fusion on fragmented knowledge.
Visualization, personalization, and recommendation of Knowledge Graph navigation and interaction.
Knowledge Graph systems and platforms, and their efficiency, scalability, and privacy.
Applications and services of knowledge discovery and graph learning in all domains including web, medicine, education, healthcare, and business.
Big knowledge systems and applications.
Crowdsourcing, deep learning and edge computing for graph mining.
Large language models and applications
Open source platforms and systems supporting knowledge and graph learning.
Survey Track
Survey paper reviewing recent study in keep aspects of knowledge discover and graph learning.In addition to the above topics, authors can also select and target the following
Special Track topics.
Each special track is handled by respective special track chairs, and the papers are also included in the conference proceedings.
Special Track 01: KGC and Knowledge Graph Building
Special Track 02: KR and KG Reasoning.
Special Track 03: KG and Large Language Model
Special Track 04: GNN and Graph Learning
Special Track 05: QA and Graph Database
Special Track 06: KG and Multi-modal Learning.
Special Track 07: KG and Knowledge Fusion.
Special Track 08: Industry and Applications
Submission Guidelines
Paper submissions should be no longer than 8 pages, in the IEEE 2-column format, including the bibliography and any possible appendices. Submissions longer than 8 pages will be rejected without review. All submissions will be reviewed by the Program Committee based on technical quality, originality, significance, and clarity. For survey track paper, please preface the descriptive paper title with “Survey:”, followed by the actual paper title. For example, a paper entitled “A Literature Review of Streaming Knowledge Graph”, should be changed as “Survey: A Literature Review of Streaming Knowledge Graph”. This is for the reviewers and chairs to clearly bid and handle the papers. Once the paper is accepted, the word, such as “Survey:”, can be removed from the camera-ready copy.
For special track paper, please preface the descriptive paper title with “SS##:”, where “##” is the two digits special track ID. For example, a paper entitled “Incremental Knowledge Graph Learning”, intended to target Special Track 01 (Machine learning and knowledge graph) should be changed as “SS01: Incremental Knowledge Graph Learning”.
All manuscripts are submitted as full papers and are reviewed based on their scientific merit. The reviewing process is single blind, meaning that each submission should list all authors and affiliations. There is no separate abstract submission step. There are no separate industrial, application, or poster tracks. Manuscripts must be submitted electronically in the online submission system. No email submission is accepted.To help ensure correct formatting, please use the style files for U.S. Letter as template for your submission. These include LaTeX and Word.Key DatesImportant Dates of the Conference.
With very best regards! Huajun
On behalf of the OC committe of ICKG2024