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The 1st International Workshop on Machine Reasoning: International Machine Reasoning Conference (MRC 2021)

Published: 08 March 2021 Publication History

Abstract

Recent years have witnessed the success of machine learning and especially deep learning in many research areas such as Vision and Language Processing, Information Retrieval and Recommender Systems, Social Networks and Conversational Agents. Though various learning approaches have demonstrated satisfying performance in perceptual tasks such as associative learning and matching by extracting useful similarity patterns from data, the area still sees a large amount of research needed to advance the ability of reasoning towards cognitive intelligence in the coming years. This includes but is not limited to neural logical reasoning, neural-symbolic reasoning, causal reasoning, knowledge reasoning and commonsense reasoning. The workshop focuses on the research of machine reasoning techniques and their application in various intelligent tasks. It will gather researchers as well as practitioners in the field for discussions, idea communications, and research promotions. It will also generate insightful debates about the recent progress in machine intelligence to a broader community, including but not limited to CV, IR, NLP, ML, DM, AI and beyond.

References

[1]
Hanxiong Chen, Shaoyun Shi, Yunqi Li, and Yongfeng Zhang. 2020. Neural Collaborative Reasoning. arXiv preprint arXiv:2005.08129 (2020).
[2]
Shaoyun Shi, Hanxiong Chen, Weizhi Ma, Jiaxin Mao, Min Zhang, and Yongfeng Zhang. 2020. Neural Logic Reasoning. CIKM (2020).
[3]
Y. Xian, Z. Fu, S Muthukrishnan, G. De Melo, and Y. Zhang. 2019. Reinforcement knowledge graph reasoning for explainable recommendation. In SIGIR. 285--294.
[4]
Y. Xian, Z. Fu, H. Zhao, Y. Ge, X. Chen, Q. Huang, S. Geng, Z. Qin, G. de Melo, S. Muthukrishnan, and Y. Zhang. 2020. CAFE: Coarse-to-Fine Neural Symbolic Reasoning for Explainable Recommendation. CIKM (2020).
[5]
S. Xu, Y. Li, S. Liu, Z. Fu, and Y. Zhang. 2020. Learning Post-Hoc Causal Explanations for Recommendation. arXiv preprint arXiv:2006.16977 (2020).

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  • (2021)CSR 2021: The 1st International Workshop on Causality in Search and RecommendationProceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3404835.3462817(2677-2680)Online publication date: 11-Jul-2021

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    cover image ACM Conferences
    WSDM '21: Proceedings of the 14th ACM International Conference on Web Search and Data Mining
    March 2021
    1192 pages
    ISBN:9781450382977
    DOI:10.1145/3437963
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    New York, NY, United States

    Publication History

    Published: 08 March 2021

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    Author Tags

    1. artificial intelligence
    2. machine reasoning

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    WSDM '21

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    Overall Acceptance Rate 498 of 2,863 submissions, 17%

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    • (2021)CSR 2021: The 1st International Workshop on Causality in Search and RecommendationProceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3404835.3462817(2677-2680)Online publication date: 11-Jul-2021

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