[image 04551] [CFP] 国際ワークショップThe 1st International Workshop on Multimodal Understanding for the Web and Social Media開催のご案内

Marc A. Kastner mkastner @ nii.ac.jp
2021年 12月 2日 (木) 15:56:50 JST


Image-MLの皆様

お世話になっております。
国立情報学研究所のマークです。

国際ワークショップThe 1st International Workshop on Multimodal Understanding for the Web and Social Media (MUWS2022)の開催案内を送らせていただきます。

詳細は下記のホームページまたは添付のCFP案内を参照してください。
https://muws-workshop.github.io

奮って投稿していただければ幸いです。

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(Apologies for possible cross-posting)
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CALL FOR PAPERS
MUWS 2022 - The 1st International Workshop on Multimodal Understanding for the Web and Social Media
co-located with The Web Conference (WWW) 2022

April 25-29 2022, Lyon, France
More Info: https://muws-workshop.github.io/
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Aim and Scope

MUWS Workshop is a forum bringing together researchers and practitioners from the fields of Information Retrieval, Natural Language Processing, Computer Vision, Human Computation, and Semiotics to discuss and evaluate methods and solutions for effective and efficient analytics of multimodal information present in the Web or social media.

We are interested in approaches, tasks, and metrics for effectively analysing multimedia information such as image-text pairs and videos to design methodologies that jointly consider information from multiple modalities. The interdisciplinary nature of processing such multimodal data involves combining ideas and methods from the fields mentioned above. We envision the workshop as a forum for researchers and practitioners from academia and industry for original contributions and practical application on multimodal information processing, mining, retrieval, search, and management. This workshop also aims to explore these semantic relations theoretically and computationally in conjunction with existing computational multimodal research.

Particular areas of interest include, but are not limited to:

    - Multimodal Event Detection, and Understanding
    - Multimodal News Analytics
    - Multimodal Sentiment Analysis
    - Multimodal Emotion Recognition
    - Multimodal Sarcasm Detection
    - Multimodal Hate Speech Detection
    - Misinformation Detection for Multimodal Data
    - Unsupervised, Self-supervised, or Semi-supervised Learning for Multimodal Data
    - Multimodal Question Answering Systems
    - Image-text Relations, Cross-modal Relations
    - Semantic Relations (semiotics)
    - Multimodal Rhetoric in Online Media


Submission Instructions

	The proceedings of the workshops will be published in The WebConf proceedings (companion volume). Workshop papers should not have been previously published, should not be considered for publication, and should not be under review for another workshop, conference, or journal. They should be no more than 12 pages in length (maximum 8 pages for the main paper content + maximum 2 pages for appendixes + maximum 2 pages for references). Papers must be submitted in PDF according to the ACM format published in the ACM guidelines, selecting the generic ‘sigconf' sample. The PDF files must have all non-standard fonts embedded. Workshop papers must be self-contained and in English.

	Submission Page: https://easychair.org/conferences/?conf=muws2022


Important Dates
	
    Submission deadline: February 3, 2022. (AoE)
    Notification of acceptance: March 3, 2022.
    Camera-ready copy due: March 10, 2022.
    Workshop day: April 25, 2022.


Organizing Committee

	Sherzod Hakimov, TIB - Leibniz Information Centre for Science and Technology, Hannover, Germany
	Gullal S. Cheema, TIB - Leibniz Information Centre for Science and Technology, Hannover, Germany
	Marc A. Kastner, National Institute of Informatics (NII), Tokyo, Japan
	Rajiv Ratn Shah, Indraprastha Institute of Information Technology, Delhi, India
	Karan Sikka, Center for Vision Technologies, SRI International in Princeton, USA

Contact

	All questions about the workshop should be emailed to: muws2022 (at sign) easychair.org


-- 
Dr. Marc A. Kastner
Postdoctoral researcher, Shin'ichi Satoh Laboratory
National Institute of Informatics, Japan
https://www.marc-kastner.com/


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