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=================== Call for papers ================== Springer special Issue in Annals of Mathematics and Artificial Intelligence Analogies: from Mathematical Foundations to Applications and Interactions with ML and AI Guest Editors: Miguel Couceiro, University of Lorraine, CNRS, Loria, France (miguel.couce...@loria.fr) Esteban Marquer, University of Lorraine, CNRS, Loria, France (esteban.marq...@loria.fr) Pierre Monnin, Orane Labs (pierre.mon...@orange.com) Pierre-Alexandre Murena, University of Helsinki (pierre-alexandre.mur...@helsinki.fi) ================================================== Motivation: Analogical reasoning is a remarkable capability of human reasoning, used to solve hard reasoning tasks. It consists in transferring knowledge from a source domain to a different, but somewhat similar, target domain by relying simultaneously on similarities and dissimilarities. In particular, analogical proportions are the basis of analogical inference and they contribute to case-based reasoning and to multiple machine learning tasks such as classification and decision making. They are applied on NLP tasks such as automatic machine translation, semantic and morphological tasks, as well as visual question answering with competitive results. Moreover, analogical extrapolation can support dataset augmentation (analogical extension) for model learning, especially in environments with few labeled examples. However, other less explored applications could be envisioned such as knowledge discovery and management (e.g., knowledge graphs refinement, data set completion, and alignment), recommender systems, and other AI-related tasks. This special issue welcomes substantial contributions in the form of (i) original research papers, (ii) extended versions of contributions to the workshops IARML@IJCAI-ECAI (https://iarml2022-ijcai-ecai.loria.fr/) and ATA@ICCBR (https://iccbr-ata2022.loria.fr/), (iii) position papers that establish interactions between analogical reasoning and machine learning, or (iv) discussion papers that highlight emerging trends or new methodologies and algorithmic tools towards analogy based reasoning, machine learning and AI. Contents: Topics of interest include, but are not limited to: – Foundational theory of analogies • Axiomatic approaches to analogical proportions; • Analogy-preserving functions; • Interactions between analogical reasoning and other forms of reasoning. – Analogical reasoning for machine learning • Analogy-based classification; • Analogy-based Recommendation; • Case-based reasoning. – Machine learning for analogical reasoning • Representation learning for analogical reasoning; • Transfer learning for analogical reasoning; • Neuro-symbolic models for analogical inference. – Applications • Analogical reasoning in visual domains; • Analogical reasoning in Natural Language Processing; • Analogical reasoning in healthcare; • Analogies in software engineering; • Analogies in knowledge management. Guidelines & Schedule: Prospective authors are invited to contact the guest editors with a declaration of intention of a proposed paper via email (miguel.couce...@loria.fr, esteban.marq...@loria.fr, pierre.mon...@orange.com, pierre-alexandre.mur...@helsinki.fi) before submitting the full paper. Submission of full papers is via the AMAI electronic submission system (https://www.editorialmanager.com/amai/default2.aspx). Further information will be sent in due time. Important Dates: - November 30, 2022: Declaration of intention – January 31, 2023: Preliminary abstract – February 28, 2023: Deadline for manuscript submission – June 30, 2023: Paper reviews – September 30, 2023: Deadline for revised manuscripts – November 30, 2023: Final decisions – December 15, 2023: Camera ready submission ==================================================
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