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First Call for Papers - 2nd International Joint Conference on Conceptual Knowledge Structures (CONCEPTS 2025)

by Peggy Cellier

*2nd International Joint Conference on Conceptual Knowledge Structures (CONCEPTS 2025)* *Cluj-Napoca, România- September, 8th-12th, 2025* *https://concepts2025.conference.ubbcluj.ro/ <https://concepts2025.conference.ubbcluj.ro/>* 29th Intl. Conf. on Conceptual Structures (ICCS) 19th Intl. Conf. on Formal Concept Analysis (ICFCA) 18th Intl. Conf. on Concept Lattices and their Applications (CLA) CONCEPTS, the International Conference on Conceptual Knowledge Structures is a merger of the three conferences CLA, ICCS, and ICFCA, which have been essential venues for researchers and practitioners working on theoretical and applied aspects of formal concept analysis and representation of conceptual knowledge, as well as closely related areas, such as data mining, information retrieval, knowledge management, and discovery. CONCEPTS 2025, the second conference in this new series, aims to continue the tradition and standards of previous conferences and to become a key annual meeting for all members of the three communities, CLA, ICCS, and ICFCA, to keep abreast of the advances and new challenges in the field. Main topics include but are not limited to: * Fundamental aspects of Formal Concept Analysis (e.g., FCA theory, concept lattices, algorithms and computational complexity) * Conceptual graphs, graph-based models for human reasoning * Knowledge spaces and learning spaces * Fuzzy, relational, and/or triadic conceptual structures * Conceptual knowledge acquisition, management, exploration, analysis, and/or visualization * Probabilistic or approximative approaches to conceptual knowledge * Bridging conceptual structures to information sciences, artificial intelligence, data mining, machine learning, information retrieval, database theory, software engineering, and other areas of computer science * Ontologies, semantic web, knowledge graphs, and their relation to conceptual knowledge structures such as concept lattices and conceptual graphs. * Conceptual structures in natural language processing and linguistics * Understanding real-world data and modeling real-world phenomena with conceptual structures (e.g., applications in digital humanities, cybersecurity, biology, medicine, social network analysis) * Psychology, philosophy, and conceptual structures. *Submission details:* Submissions are invited on significant, original (previously unpublished) research on the topics of the conference: * Journal-track papers up to 26 pages, to be published in a special issue of the<https://www.sciencedirect.com/journal/international-journal-of-approximate-…>International Journal of Approximate Reasoning (IJAR) <https://www.sciencedirect.com/journal/international-journal-of-approximate-…>; * Regular papers up to 16 pages and short papers up to 8 pages are to be published by Springer in the LNAI series as a proceedings volume. All submissions will be subject to single-blind peer review. Accepted papers have to be presented at the conference on-site. Therefore, at least one author per paper has to register timely and attend the conference on-site. *Important dates and submission instructions:* /***Journal-track submissions***/ - Full paper submission: *March 16, 2025 (AoE)* - Paper reviews sent to authors: *May 2nd, 2025* - Revised submission: *June 2, 2025* - Notification of acceptance: *June 29, 2025* Details about the submission system and the guidelines to authors will be provided shortly. /***Regular and short papers***/ - Abstract submission: *March 17, 2025 (AoE)* - Full paper submission: *March 24, 2025 (AoE)* - Notification of acceptance: *May 14, 2025* - Camera-ready papers due: *May 29, 2025* Submission link:<https://equinocs.springernature.com/home>https://equinocs.springernature.com/home <https://equinocs.springernature.com/home> Please select the appropriate category for your submitted manuscript, “regular paper” or “short paper.” Please visit the page<https://www.springer.com/gp/computer-science/lncs/conference-proceedings-gu…>Information for authors <https://www.springer.com/gp/computer-science/lncs/conference-proceedings-gu…> on Springer's website for templates and formatting style. *Organization:* _General and Conference Chair:_ Christian Săcărea, Babeș-Bolyai University, Romania _Program Chairs:_ Peggy Cellier, IRISA/INSA Rennes, France Bernhard Ganter, TU Dresden, Germany Rokia Missaoui, Université du Québec en Outaouais, Canada _Local organizer Committee:_ Christian Săcărea, Babeș-Bolyai University, Cluj-Napoca, România Diana Cristea, Babeș-Bolyai University, Cluj-Napoca, Diana Șotropa, Babeș-Bolyai University, Cluj-Napoca _Executive Board:_ Jaume Baixeries, Polytechnic University of Catalonia, Spain Radim Belohlavek, Palacký University Olomouc, Czech Republic Tanya Braun, University of Münster, Germany Madalina Croitoru, University of Montpellier, France Sébastien Ferré, University of Rennes, France Sergei Kuznetsov, HSE University, Moscow, Russia Rokia Missaoui, Université du Québec en Outaouais, Canada Amedeo Napoli, LORIA, Nancy, France Sergei Obiedkov, TU Dresden, Germany Manuel Ojeda-Aciego, University of Malaga, Spain Uta Priss, Ostfalia University of Applied Sciences, Wolfenbüttel, Germany Gerd Stumme, University of Kassel, Germany _Program Committee:_ Jaume Baixeries, Polytechnic University of Catalonia, Spain Alexandre Bazin, LIRMM, Montpellier, France Mike Behrisch, Technische Universität Wien, Austria Sadok Ben Yahia, Technology University of Tallinn, Estonia Karell Bertet, La Rochelle University, France Inma P. Cabrera, Universidad de Málaga, Spain Peggy Cellier, IRISA/INSA Rennes, France Maria Eugenia Cornejo Piñero, University of Cádiz, Spain Christophe Demko, La Rochelle University, France Xavier Dolques, Université de Strasbourg, France Dominik Dürrschnabel, Universität Kassel, Germany Sébastien Ferré, IRISA université de Rennes, France Bernhard Ganter, TU Dresden, Germany Alain Gely, université de Lorraine, France Tom Hanika, University of Hildesheim, Germany Tobias Hille, University of Kassel Germany Marianne Huchard, LIRMM, Univ. Montpellier, France Mohamed Hamza Ibrahim, University of Quebec in Outaouais, Canada Dmitry Ignatov, HSE University, Moscow, Russia Mehdi Kaytoue, Infologic R&D, France Blaise Blériot Koguep Njionou, Université de Dschang, Cameroun Francesco Kriegel, TU Dresden, Germany Sergei Kuznetsov, HSE University, Moscow, Russia Leonard Kwuida, Bern University of Applied Sciences, Switzerland Florence Le Ber, Université de Strasbourg, France Pierre Martin, University of Montpellier, France Jesús Medina, University of Cádiz, Spain Rokia Missaoui, University of Quebec in Outaouais, Canada Amedeo Napoli, LORIA, Université de Lorraine, France Sergei Obiedkov, TU Dresden, Germany Manuel Ojeda-Aciego, Universidad de Málaga, Spain Jan Outrata, Palacký University Olomouc, Czech Republic Tim Pattison, Defence Science and Technology Group, Australia Carmen Peláez-Moreno, Univ. Carlos III de Madrid, Spain Uta Priss, Ostfalia Hochschule of Applied Sciences, Wolfenbüttel, Germany Sandor Radeleczki, University of Miskolc, Hungary Eloísa Ramírez Poussa, Universidad de Cádiz, Spain Sebastian Rudolph, TU Dresden, Germany Baris Sertkaya, Frankfurt University of Applied Sciences, Germany Henry Soldano, Université Paris 13, France Petko Valtchev, Université du Québec à Montréal, Canada Gerd Stumme, University of Kassel, Germany Martin Trnecka, Palacký University Olomouc, Czech Republic Francisco José Valverde-Albacete, Univ. Rey Juan Carlos, Madrid, Spain We look forward to meeting you in Cluj-Napoca. Please, feel free to contact us for any further information. Sincerely yours, Peggy Cellier, Bernhard Ganter, and Rokia Missaoui *CONCEPTS 2025 Program chairs* Email contact address: concepts25(a)lists.cs.uni-kassel.de

3 months, 1 week

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Link for coordinating first working group meeting: FCA repository

by Tom Hanika

Dear FCA Researcher, as presented today at CONCEPTS 2024 [1] we will have the first meeting of the fcarepository.org working group in November. You are invited to participate in and contribute to this new FCA endeavor. To coordinate the date we set up a calendar tool [2]. Please indicate which dates would fit for you, if you want to participate. Best regards Tom [1] https://concepts2024.uca.es/ [2] https://terminplaner6.dfn.de/p/524cbe1df59d322f67043c5ad65a6009-870853 -- Dr. Tom Hanika Universität Kassel Tel.: +49 (0) 561 804 6252 https://www.kde.cs.uni-kassel.de/hanika ---------------------------------------------------------------------

3 months, 2 weeks

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ESAO Webinar n.13 on Tuesday November 12th, 2024 16:00 CET –- Call for Participation

by Cassia TROJAHN

Dear all, The Educational Series on Applied Ontology (ESAO) [1] is open for everyone and welcomes students, researchers and practitioners alike. The 13h ESAO webinar will be held on Tuesday November 12th, 2024 at 16:00 CET. --------------------------- When and how to connect Tuesday November 12th, 2024 15:00 UTC / 16:00 CET / 17:00 SAST Duration: 60 minutes Video conference (via Zoom) : https://univ-tlse2.zoom.us/j/92895546685?pwd=DQD7Wzf3ZJw02LJ2hHmrVDwdN474PZ… --------------------------- Program 15:00 - 16:00 UTC / 16:00 - 17:00 CET / 17:00 - 18:00 SAST / 12:00 - 13:00 UTC-3 Jérôme Euzenat, INRIA & Univ. Grenoble Alpes, France Ontology evolution Abstract: Unless considering ontologies as transcendental and perfect, they need to evolve. This may be because the world they represent evolves or the purpose they fulfill requires it. In general, what triggers evolution is the inadequacy of an ontology. Restoring it may be carried out by human designers or automatic means, but it is worthwhile that they follow rules. In this short presentation, we will discuss two techniques that may help evolving ontologies: belief revision and artificial cultural evolution. How they are different and how they are alike. Best regards Cassia Trojahn, Frank Loebe, Laure Vieu On behalf of the IAOA Education Committee [1] https://wiki.iaoa.org/index.php/Edu:ESAO

4 months, 1 week

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ESAO Webinar n.12 on Tuesday October 1st, 2024 16:00 CEST –- Call for Participation

by Cassia TROJAHN

Dear all, The Educational Series on Applied Ontology (ESAO) [1] is open for everyone and welcomes students, researchers and practitioners alike. The 12h ESAO webinar will be held on Tuesday October 1st, 2024 at 16:00 CET. --------------------------- When and how to connect Tuesday October 1st, 2024 14:00 UTC / 16:00 CEST / 16:00 SAST Duration: 90 minutes Video conference (via Zoom) : https://univ-tlse2.zoom.us/j/92895546685?pwd=DQD7Wzf3ZJw02LJ2hHmrVDwdN474PZ… --------------------------- Program 14:00-15:30 UTC / 16:00-17:30 CEST / 16:00-17:30 SAST / 11:00-12:30 UTC-3 Olivier Kutz, Free University of Bozen-Bolzano, Italy Title: Concepts, concept combinations, and the tooth operator Abstract: We will discuss some of the approaches to model concepts and concept combinations with the help of logic, and illustrate how such modelling approaches are capable (or not) of modelling aspects of human reasoning with concepts. We will then explain the basic ideas underlying the framework of weighted description logics, also called perceptron or 'tooth' logic, and illustrate its key features and benefits for modelling and reasoning with concepts. Maria Hedblom, Jönköping University, Sweden Title: Cognitive foundations for KR Abstract: TBA Best regards Cassia Trojahn, Frank Loebe, Laure Vieu On behalf of the IAOA Education Committee [1] https://wiki.iaoa.org/index.php/Edu:ESAO

5 months, 2 weeks

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Workshop FCA4AI 2024 (Deadline extension)

by Amedeo Napoli

Sorry for duplicates. ------------------------------------------------------------------------------------------------------------------- -- FCA4AI (Twelfth Edition) -- "What can FCA do for Artificial Intelligence?'' co-located with ECAI 2024, Santiago de Compostela, Spain October 19th 2024 http://www.fca4ai.hse.ru/2024 ------------------------------------------------------------------------------------------------------------------- General Information. The eleven preceding editions of the FCA4AI Workshop (from ECAI 2012 until IJCAI 2023) showed that many researchers working in Artificial Intelligence are indeed interested in powerful techniques for classification and data mining provided by Formal Concept Analysis. The twelfth edition of FCA4AI will once more be co-located with the ECAI Conference, and thus be held in Santiago de Compostela. Formal Concept Analysis (FCA) is a mathematically well-founded theory aimed at data analysis and classification. FCA allows one to build a concept lattice and a system of dependencies (implications and association rules) which can be used for many AI needs, e.g. knowledge processing, knowledge discovery, knowledge representation and reasoning, ontology engineering as well as information retrieval, recommendation, social network analysis and text processing. Thus, there are many "natural links'' between FCA and AI. Recent years have been witnessing increased scientific activity around FCA, in particular a strand of work emerged that is aimed at extending the possibilities of plain FCA w.r.t. knowledge processing, such as work on pattern structures and relational context analysis, as well as on hybridization with other formalisms. These extensions are aimed at allowing FCA to deal with more complex than just binary data, for solving complex problems in data analysis, classification, knowledge processing, etc. While the capabilities of FCA are extended, new possibilities are arising in the framework of FCA. As usual, the FCA4AI workshop is dedicated to the discussion of such issues, and in particular: - How can FCA support AI activities in knowledge discovery, knowledge representation and reasoning, machine learning, natural language processing and others? - Vice versa, how can the current developments in AI be adopted within FCA to help AI researchers solve complex problems in their domain? - Which role can FCA play in the new trends in AI, especially in ML, XAI, fairness of algorithms, and "hybrid systems'' combining symbolic and subsymbolic approaches? TOPICS OF INTEREST include but are not limited to: - Concept lattices and related structures: pattern structures, relational structures, distributive lattices. - Knowledge discovery and data mining: pattern mining, association rules, attribute implications, subgroup discovery, exceptional model mining, data dependencies, attribute exploration, stability, projections, interestingness measures, MDL principle, mining of complex data, triadic and polyadic analysis. - Knowledge and data engineering: knowledge representation, reasoning, ontology engineering, mining the web of data, text mining, data quality checking. - Analyzing the potential of FCA in supporting hybrid systems: how to combine FCA and data mining algorithms, such as deep learning for building hybrid knowledge discovery systems, producing explanations, and assessing system fairness. - Analyzing the potential of FCA in AI tasks such as classification, clustering, biclustering, information retrieval, navigation, recommendation, text processing, visualization, pattern recognition, analysis of social networks. - FCA and Large Language Models (LLMs). - Practical applications in agronomy, astronomy, biology, chemistry, finance, manufacturing, medicine, and others. The workshop will include time for audience discussion aimed at a better understanding of the issues, challenges, and ideas being presented. IMPORTANT DATES: Submission deadline: September 08 2024 Notification to authors: September 23 2024 Final version: October 06 2024 Workshop: October 19 2024 SUBMISSION DETAILS: The workshop welcomes submissions in pdf format following the CEURART style 1-column (to be downloaded at https://ceur-ws.org/Vol-XXX/CEURART.zip). Submissions can be: - technical papers between 8 and 12 pages, - system descriptions or position papers describing work in progress not exceeding 6 pages. Submissions are via EasyChair at https://easychair.org/conferences/?conf=fca4ai2024 The workshop proceedings will be published as CEUR proceedings (see preceding editions in CEUR Proceedings Vol-3489, Vol-3233, Vol-2972, Vol-2729, Vol-2529, Vol-2149, Vol-1703, Vol-1430, Vol-1257, Vol-1058, and Vol-939). WORKSHOP CHAIRS: Sergei O. Kuznetsov National Research University Higher Schools of Economics, Moscow, Russia Amedeo Napoli Université de Lorraine, CNRS, Inria, LORIA, Nancy, France Sebastian Rudolph Technische Universität Dresden, Germany PROGRAM COMMITTEE (under construction) ------------------------------------------------------------------------------------------------------------------- -------------------------------------------------------------------------------------------------------------------

6 months, 2 weeks

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Second Rostock Open Science Workshop

by MPIDR - Career

Open science aims to make research results and materials freely accessible to everyone, with the goal of increasing knowledge circulation, increasing transparency, and providing the means to reproduce and generalize published findings. Venue: Max Planck Institute for Demographic Research (MPIDR), Rostock, Germany Dates: March 17-18, 2025 Website: https://www.demogr.mpg.de/en/news_events_6123/calendar_1921/second_rostock_… -- This mail has been sent through the MPI for Demographic Research. Should you receive a mail that is apparently from a MPI user without this text displayed, then the address has most likely been faked. If you are uncertain about the validity of this message, please check the mail header or ask your system administrator for assistance.

7 months, 1 week

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[KaRS 2024] 3rd CfP: 6th Knowledge-aware and Conversational Recommender Systems Workshop 2024 @ ACM RecSys

by Vito Walter Anelli

3rd Call for Papers Sixth Knowledge-aware and Conversational Recommender Systems Workshop (KaRS 2024) https://kars-workshop.github.io/2024/ Oct. 14th - Oct. 18th, 2024, Bari Submission deadline: August 30th, 2024, AoE We are pleased to invite you to contribute to the Sixth Knowledge-aware and Conversational Recommender Systems Workshop held in conjunction with the ACM International Conference on Recommender Systems (RecSys 2024), Bari, Italy, from October the 14th to October the 18th, 2024. # Scope Recommender systems have achieved ubiquity across various domains, ranging from e-commerce to media content suggestions, playing pivotal roles in facilitating user online experiences. However, despite their prevalence, these systems often encounter challenges in effectively engaging with human users. While data-driven algorithms have demonstrated success in uncovering latent connections within user-item interactions, they frequently overlook the central actor in this loop: the end-user. A prevalent behavior among human users, which is rarely encoded in recommendation engines, is the utilization of domain-specific knowledge. Fortunately, Knowledge-aware Recommender Systems are garnering increasing attention within the recommendation community. By leveraging explicit domain knowledge represented via ontologies or knowledge graphs, these approaches can understand the semantic relationships between users, items, and other entities, thus offering tailored recommendations to users and addressing inherent limitations of purely data-driven systems. Despite their existence for over two decades, their significance has been revitalized due to the Linked Open Data initiative and the availability of large knowledge-graphs such as DBpedia and Wikidata. Linked data and their ontologies underpin many recommendation approaches and challenges proposed in recent years, such as Knowledge Graph embeddings, hybrid recommendation, link prediction, knowledge transfer, interpretable recommendation, and user modeling. Moreover, a new wave in this domain is marked by the emergence of neuro-symbolic systems, integrating data-driven methodologies with symbolic reasoning. This fusion of machine learning systems, adept at harnessing data, with symbolic approaches, adept at leveraging knowledge, holds promise in enhancing recommendation quality, particularly in scenarios with sparse training data. In parallel, the rise of Conversational Recommender Systems (CRSs) highlights the crucial role of content features in facilitating user interactions, particularly in multi-turn dialogues between users and the system, which bring about novel challenges, such as the incorporation of both short- and long-term preferences, prompt adaptation to user feedback, the limited availability of datasets, and the evaluation beyond simple accuracy metrics. In this context, the emergence of Large Language Models (LLMs) is pivotal and has breathed new life into CRSs. LLMs significantly impact CRSs by leveraging their advanced capabilities in understanding user queries and generating relevant recommendations in natural language. They excel in processing complex and nuanced user inputs, allowing for more seamless and engaging interactions between users and the system. Moreover, LLMs contribute to the adaptability and responsiveness of CRSs by continuously learning from user interactions, thus refining their recommendations and improving the user experience over time. The **Sixth Knowledge-aware and Conversational Recommender Systems (KaRS) Workshop** aims to spark a new generation of research that prioritizes user experience, engagement, and satisfaction over mere accuracy. Drawing upon a multifaceted set of expertise including **Machine Learning**, **Deep Learning**, **Human-Computer Interaction**, **Information Retrieval**, and **Information Systems**, this workshop endeavors to catalyze a fresh wave of research. KaRS serves as a dynamic forum where researchers and practitioners, scholars and industry professionals, converge to not only disseminate their latest findings but also to identify the emerging topics, delineate the next key challenges, and forecast the future opportunities for research and development. Through fostering active participation and facilitating the exchange of ideas, KaRS aims to cultivate an interdisciplinary community that collaborates on the topics of knowledge-aware and conversational recommenders, alongside the emerging topics of LLMs and neuro-symbolic methodologies, which further extend the scope of this new edition of KaRS. # Topics This workshop aims at establishing an interdisciplinary community with a focus on the exploitation of (semi-)structured knowledge and conversational approaches for recommender systems and promoting collaboration opportunities between researchers and practitioners. Topics of interest include, but are not limited to: - **Knowledge-aware Recommender Systems**. - Models and Feature Engineering: - Knowledge-aware data models based on structured knowledge sources (e.g., Linked Open Data, BabelNet, Wikidata, etc.) - Semantics-aware approaches exploiting the analysis of textual sources (e.g., Wikipedia, Social Web, etc.) - Knowledge-aware user modeling - Methodological aspects (evaluation protocols, metrics, and data sets) - Logic-based modeling of a recommendation process - Knowledge Representation and Automated Reasoning for recommendation engines - Deep learning methods to model semantic features - Large language models (LLMs) for Knowledge-aware Recommender Systems - Beyond-Accuracy Recommendation Quality: - Using knowledge bases and knowledge graphs to increase recommendation quality(e.g., in terms of novelty, diversity, serendipity, or explainability) - Explainable Recommender Systems - Knowledge-aware explanations to recommendations (compliant with the General Data Protection Regulation) - Online Studies: - Using knowledge sources for cross-lingual recommendations - Applications of knowledge-aware recommenders (e.g., music or news recommendation, off-mainstream application areas) - User studies (e.g., on the user's perception of knowledge-based recommendations), field studies, in-depth experimental offline evaluations - **Conversational Recommender Systems**. - Design of a Conversational Agent: - Design and implementation methodologies - Dialogue management (end-to-end, dialog-state-tracker models) - UX design - Dialog protocols design - Large language models (LLMs) for Conversational Recommender Systems - User Modeling and interfaces: - Critiquing and user feedback exploitation - Short- and Long-term user profiling and modeling - Preference elicitation - Natural language-, multi-modal-, and voice-based interfaces - Next-question problem - Methodological and Theoretical aspects: - Evaluation and metrics - Datasets - Theoretical aspects of conversational recommender systems # Submissions We invite three kinds of submissions, which address novel issues in Knowledge-aware and Conversational Recommender Systems: * **Long Papers** should report on substantial contributions of lasting value. **The Long papers must have a length of a minimum of 6 and a maximum of 8 pages (plus an unlimited number of pages for references)**. * **Short/Demo Papers** typically discuss exciting new work that is not yet mature enough for a long paper. In particular, novel but significant proposals will be considered for acceptance in this category despite not having gone through sufficient experimental validation or lacking a strong theoretical foundation. Applications of recommender systems to novel areas are especially welcome. **The Short/Demo papers must have a length of a minimum of 3 and a maximum of 5 pages (plus an unlimited number of pages for references)**. * **Position/Discussion Papers** describe novel and innovative ideas. Position papers may also comprise an analysis of currently unsolved problems, or review these problems from a new perspective, in order to contribute to a better understanding of these problems in the research community. We expect that such papers will guide future research by highlighting critical assumptions, motivating the difficulty of a certain problem, or explaining why current techniques are not sufficient, possibly corroborated by quantitative and qualitative arguments. **The Position/Discussion papers must have a length of a minimum of 2 and a maximum of 3 pages (plus an unlimited number of pages for references)**. Papers may range from theoretical works to system descriptions. We particularly encourage Ph.D. students or Early-Stage Researchers to submit their research. We also welcome contributions from the industry and papers describing ongoing funded projects which may result useful to the Knowledge-aware and Conversational Recommender Systems community. Submission will be peer-reviewed and accepted papers will appear in the **workshop proceedings** (CEUR workshop series). The review process is **single-blind**. Submitted papers will be evaluated according to their originality, technical content, style, clarity, and relevance to the workshop. Long and short/demo paper submissions must be original work and may not be under submission to another venue at the time of review. Each accepted long or short paper will be included in the CEUR online Workshop proceedings and presented in a plenary session as part of the Workshop program. Original position/discussion accepted papers will be included in the CEUR online Workshop proceedings. Selected position/discussion papers will be invited as oral presentations. Submissions of full research papers must be in English, in PDF format in the **CEUR-WS two-column conference format** available as compressed archive (http://ceur-ws.org/Vol-XXX/CEURART.zip) or as Overleaf template (https://www.overleaf.com/latex/templates/template-for-submissions-to-ceur-w…). Papers must be submitted through EasyChair (https://easychair.org/conferences/?conf=recsys2024workshops) by selecting the track "KaRS: Sixth Knowledge-aware and Conversational Recommender Systems Workshop". # Important Dates * **Paper submissions deadline**: August 30th, 2024 * **Paper acceptance notification**: September 16th, 2024 * **Camera-ready deadline**: September 30th, 2024 * **Workshop day**: October 14th-18th, 2024 Deadlines refer to 23:59 (11:59 pm) in the AoE (Anywhere on Earth) time zone. Informativa Privacy - Ai sensi del Regolamento (UE) 2016/679 si precisa che le informazioni contenute in questo messaggio sono riservate e ad uso esclusivo del destinatario. Qualora il messaggio in parola Le fosse pervenuto per errore, La preghiamo di eliminarlo senza copiarlo e di non inoltrarlo a terzi, dandocene gentilmente comunicazione. Grazie. Privacy Information - This message, for the Regulation (UE) 2016/679, may contain confidential and/or privileged information. If you are not the addressee or authorized to receive this for the addressee, you must not use, copy, disclose or take any action based on this message or any information herein. If you have received this message in error, please advise the sender immediately by reply e-mail and delete this message. Thank you for your cooperation.

7 months, 1 week

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Next ESAO webinars

by Cassia TROJAHN

Dear all, The Educational Series on Applied Ontology (ESAO) [1] is open for everyone and welcomes students, researchers and practitioners alike. Three sessions are scheduled to take place in the second semester of 2024 (details on [1]): **September 10th, 16:00 CEST** Olivier Kutz (Free University of Bozen-Bolzano, Italy) Title: TBA Maria Hedblom (Jönköping University, Sweden) Title: Cognitive foundations for KR **November 12th, 16:00 CET** Sandra Lovrencic (University of Zagreb Faculty of organization and informatics) Title: Concepts Jérôme Euzenat (INRIA & Univ. Grenoble Alpes, France) Title: Ontology evolution **December 17th, 16:00 CET** Sergio De Cesare (University of Westminster, UK) Title: Ontology-driven conceptual modelling Maria Keet (University of Cape Town, South Africa) Title: Competency questions We count on your participation! Best regards Cassia Trojahn On behalf of the ESAO organisers [1] https://wiki.iaoa.org/index.php/Edu:ESAO

7 months, 3 weeks

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Call for papers FCA4AI 12th Workshop co-located with ECAI 2024 at Santiago de Compostela, Spain

by Amedeo Napoli

Apologies for duplicates... ------------------------------------------------------------------------------------------------------------------- -- FCA4AI (Twelfth Edition) -- "What can FCA do for Artificial Intelligence?'' co-located with ECAI 2024, Santiago de Compostela, Spain October 19th 2024 http://www.fca4ai.hse.ru/2024 ------------------------------------------------------------------------------------------------------------------- General Information. The eleven preceding editions of the FCA4AI Workshop (from ECAI 2012 until IJCAI 2023) showed that many researchers working in Artificial Intelligence are indeed interested in powerful techniques for classification and data mining provided by Formal Concept Analysis. The twelfth edition of FCA4AI will once more be co-located with the ECAI Conference, and thus be held in Santiago de Compostela. Formal Concept Analysis (FCA) is a mathematically well-founded theory aimed at data analysis and classification. FCA allows one to build a concept lattice and a system of dependencies (implications and association rules) which can be used for many AI needs, e.g. knowledge processing, knowledge discovery, knowledge representation and reasoning, ontology engineering as well as information retrieval, recommendation, social network analysis and text processing. Thus, there are many "natural links'' between FCA and AI. Recent years have been witnessing increased scientific activity around FCA, in particular a strand of work emerged that is aimed at extending the possibilities of plain FCA w.r.t. knowledge processing, such as work on pattern structures and relational context analysis, as well as on hybridization with other formalisms. These extensions are aimed at allowing FCA to deal with more complex than just binary data, for solving complex problems in data analysis, classification, knowledge processing, etc. While the capabilities of FCA are extended, new possibilities are arising in the framework of FCA. As usual, the FCA4AI workshop is dedicated to the discussion of such issues, and in particular: - How can FCA support AI activities in knowledge discovery, knowledge representation and reasoning, machine learning, natural language processing and others? - Vice versa, how can the current developments in AI be adopted within FCA to help AI researchers solve complex problems in their domain? - Which role can FCA play in the new trends in AI, especially in ML, XAI, fairness of algorithms, and "hybrid systems'' combining symbolic and subsymbolic approaches? TOPICS OF INTEREST include but are not limited to: - Concept lattices and related structures: pattern structures, relational structures, distributive lattices. - Knowledge discovery and data mining: pattern mining, association rules, attribute implications, subgroup discovery, exceptional model mining, data dependencies, attribute exploration, stability, projections, interestingness measures, MDL principle, mining of complex data, triadic and polyadic analysis. - Knowledge and data engineering: knowledge representation, reasoning, ontology engineering, mining the web of data, text mining, data quality checking. - Analyzing the potential of FCA in supporting hybrid systems: how to combine FCA and data mining algorithms, such as deep learning for building hybrid knowledge discovery systems, producing explanations, and assessing system fairness. - Analyzing the potential of FCA in AI tasks such as classification, clustering, biclustering, information retrieval, navigation, recommendation, text processing, visualization, pattern recognition, analysis of social networks. - FCA and Large Language Models (LLMs). - Practical applications in agronomy, astronomy, biology, chemistry, finance, manufacturing, medicine, and others. The workshop will include time for audience discussion aimed at a better understanding of the issues, challenges, and ideas being presented. IMPORTANT DATES: Submission deadline: August 25 2024 Notification to authors: September 16 2024 Final version: October 06 2024 Workshop: October 19 2024 SUBMISSION DETAILS: The workshop welcomes submissions in pdf format following the CEURART style 1-column (to be downloaded at https://ceur-ws.org/Vol-XXX/CEURART.zip). Submissions can be: - technical papers between 8 and 12 pages, - system descriptions or position papers describing work in progress not exceeding 6 pages. Submissions are via EasyChair at https://easychair.org/conferences/?conf=fca4ai2024 The workshop proceedings will be published as CEUR proceedings (see preceding editions in CEUR Proceedings Vol-3489, Vol-3233, Vol-2972, Vol-2729, Vol-2529, Vol-2149, Vol-1703, Vol-1430, Vol-1257, Vol-1058, and Vol-939). WORKSHOP CHAIRS: Sergei O. Kuznetsov National Research University Higher Schools of Economics, Moscow, Russia Amedeo Napoli Université de Lorraine, CNRS, Inria, LORIA, Nancy, France Sebastian Rudolph Technische Universität Dresden, Germany PROGRAM COMMITTEE (under construction) ------------------------------------------------------------------------------------------------------------------- -------------------------------------------------------------------------------------------------------------------

7 months, 4 weeks

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[KaRS 2024] 2nd CfP: 6th Knowledge-aware and Conversational Recommender Systems Workshop 2024 @ ACM RecSys

by Vito Walter Anelli

2nd Call for Papers Sixth Knowledge-aware and Conversational Recommender Systems Workshop (KaRS 2024) https://kars-workshop.github.io/2024/ Oct. 14th - Oct. 18th, 2024, Bari Submission deadline: August 30th, 2024, AoE We are pleased to invite you to contribute to the Sixth Knowledge-aware and Conversational Recommender Systems Workshop held in conjunction with the ACM International Conference on Recommender Systems (RecSys 2024), Bari, Italy, from October the 14th to October the 18th, 2024. # Scope Recommender systems have achieved ubiquity across various domains, ranging from e-commerce to media content suggestions, playing pivotal roles in facilitating user online experiences. However, despite their prevalence, these systems often encounter challenges in effectively engaging with human users. While data-driven algorithms have demonstrated success in uncovering latent connections within user-item interactions, they frequently overlook the central actor in this loop: the end-user. A prevalent behavior among human users, which is rarely encoded in recommendation engines, is the utilization of domain-specific knowledge. Fortunately, Knowledge-aware Recommender Systems are garnering increasing attention within the recommendation community. By leveraging explicit domain knowledge represented via ontologies or knowledge graphs, these approaches can understand the semantic relationships between users, items, and other entities, thus offering tailored recommendations to users and addressing inherent limitations of purely data-driven systems. Despite their existence for over two decades, their significance has been revitalized due to the Linked Open Data initiative and the availability of large knowledge-graphs such as DBpedia and Wikidata. Linked data and their ontologies underpin many recommendation approaches and challenges proposed in recent years, such as Knowledge Graph embeddings, hybrid recommendation, link prediction, knowledge transfer, interpretable recommendation, and user modeling. Moreover, a new wave in this domain is marked by the emergence of neuro-symbolic systems, integrating data-driven methodologies with symbolic reasoning. This fusion of machine learning systems, adept at harnessing data, with symbolic approaches, adept at leveraging knowledge, holds promise in enhancing recommendation quality, particularly in scenarios with sparse training data. In parallel, the rise of Conversational Recommender Systems (CRSs) highlights the crucial role of content features in facilitating user interactions, particularly in multi-turn dialogues between users and the system, which bring about novel challenges, such as the incorporation of both short- and long-term preferences, prompt adaptation to user feedback, the limited availability of datasets, and the evaluation beyond simple accuracy metrics. In this context, the emergence of Large Language Models (LLMs) is pivotal and has breathed new life into CRSs. LLMs significantly impact CRSs by leveraging their advanced capabilities in understanding user queries and generating relevant recommendations in natural language. They excel in processing complex and nuanced user inputs, allowing for more seamless and engaging interactions between users and the system. Moreover, LLMs contribute to the adaptability and responsiveness of CRSs by continuously learning from user interactions, thus refining their recommendations and improving the user experience over time. The **Sixth Knowledge-aware and Conversational Recommender Systems (KaRS) Workshop** aims to spark a new generation of research that prioritizes user experience, engagement, and satisfaction over mere accuracy. Drawing upon a multifaceted set of expertise including **Machine Learning**, **Deep Learning**, **Human-Computer Interaction**, **Information Retrieval**, and **Information Systems**, this workshop endeavors to catalyze a fresh wave of research. KaRS serves as a dynamic forum where researchers and practitioners, scholars and industry professionals, converge to not only disseminate their latest findings but also to identify the emerging topics, delineate the next key challenges, and forecast the future opportunities for research and development. Through fostering active participation and facilitating the exchange of ideas, KaRS aims to cultivate an interdisciplinary community that collaborates on the topics of knowledge-aware and conversational recommenders, alongside the emerging topics of LLMs and neuro-symbolic methodologies, which further extend the scope of this new edition of KaRS. # Topics This workshop aims at establishing an interdisciplinary community with a focus on the exploitation of (semi-)structured knowledge and conversational approaches for recommender systems and promoting collaboration opportunities between researchers and practitioners. Topics of interest include, but are not limited to: - **Knowledge-aware Recommender Systems**. - Models and Feature Engineering: - Knowledge-aware data models based on structured knowledge sources (e.g., Linked Open Data, BabelNet, Wikidata, etc.) - Semantics-aware approaches exploiting the analysis of textual sources (e.g., Wikipedia, Social Web, etc.) - Knowledge-aware user modeling - Methodological aspects (evaluation protocols, metrics, and data sets) - Logic-based modeling of a recommendation process - Knowledge Representation and Automated Reasoning for recommendation engines - Deep learning methods to model semantic features - Large language models (LLMs) for Knowledge-aware Recommender Systems - Beyond-Accuracy Recommendation Quality: - Using knowledge bases and knowledge graphs to increase recommendation quality(e.g., in terms of novelty, diversity, serendipity, or explainability) - Explainable Recommender Systems - Knowledge-aware explanations to recommendations (compliant with the General Data Protection Regulation) - Online Studies: - Using knowledge sources for cross-lingual recommendations - Applications of knowledge-aware recommenders (e.g., music or news recommendation, off-mainstream application areas) - User studies (e.g., on the user's perception of knowledge-based recommendations), field studies, in-depth experimental offline evaluations - **Conversational Recommender Systems**. - Design of a Conversational Agent: - Design and implementation methodologies - Dialogue management (end-to-end, dialog-state-tracker models) - UX design - Dialog protocols design - Large language models (LLMs) for Conversational Recommender Systems - User Modeling and interfaces: - Critiquing and user feedback exploitation - Short- and Long-term user profiling and modeling - Preference elicitation - Natural language-, multi-modal-, and voice-based interfaces - Next-question problem - Methodological and Theoretical aspects: - Evaluation and metrics - Datasets - Theoretical aspects of conversational recommender systems # Submissions We invite three kinds of submissions, which address novel issues in Knowledge-aware and Conversational Recommender Systems: * **Long Papers** should report on substantial contributions of lasting value. **The Long papers must have a length of a minimum of 6 and a maximum of 8 pages (plus an unlimited number of pages for references)**. * **Short/Demo Papers** typically discuss exciting new work that is not yet mature enough for a long paper. In particular, novel but significant proposals will be considered for acceptance in this category despite not having gone through sufficient experimental validation or lacking a strong theoretical foundation. Applications of recommender systems to novel areas are especially welcome. **The Short/Demo papers must have a length of a minimum of 3 and a maximum of 5 pages (plus an unlimited number of pages for references)**. * **Position/Discussion Papers** describe novel and innovative ideas. Position papers may also comprise an analysis of currently unsolved problems, or review these problems from a new perspective, in order to contribute to a better understanding of these problems in the research community. We expect that such papers will guide future research by highlighting critical assumptions, motivating the difficulty of a certain problem, or explaining why current techniques are not sufficient, possibly corroborated by quantitative and qualitative arguments. **The Position/Discussion papers must have a length of a minimum of 2 and a maximum of 3 pages (plus an unlimited number of pages for references)**. Papers may range from theoretical works to system descriptions. We particularly encourage Ph.D. students or Early-Stage Researchers to submit their research. We also welcome contributions from the industry and papers describing ongoing funded projects which may result useful to the Knowledge-aware and Conversational Recommender Systems community. Submission will be peer-reviewed and accepted papers will appear in the **workshop proceedings** (CEUR workshop series). The review process is **single-blind**. Submitted papers will be evaluated according to their originality, technical content, style, clarity, and relevance to the workshop. Long and short/demo paper submissions must be original work and may not be under submission to another venue at the time of review. Each accepted long or short paper will be included in the CEUR online Workshop proceedings and presented in a plenary session as part of the Workshop program. Original position/discussion accepted papers will be included in the CEUR online Workshop proceedings. Selected position/discussion papers will be invited as oral presentations. Submissions of full research papers must be in English, in PDF format in the **CEUR-WS two-column conference format** available as compressed archive (http://ceur-ws.org/Vol-XXX/CEURART.zip) or as Overleaf template (https://www.overleaf.com/latex/templates/template-for-submissions-to-ceur-w…). Papers must be submitted through EasyChair (https://easychair.org/conferences/?conf=recsys2024workshops) by selecting the track "KaRS: Sixth Knowledge-aware and Conversational Recommender Systems Workshop". # Important Dates * **Paper submissions deadline**: August 30th, 2024 * **Paper acceptance notification**: September 16th, 2024 * **Camera-ready deadline**: September 30th, 2024 * **Workshop day**: October 14th-18th, 2024 Deadlines refer to 23:59 (11:59 pm) in the AoE (Anywhere on Earth) time zone. Informativa Privacy - Ai sensi del Regolamento (UE) 2016/679 si precisa che le informazioni contenute in questo messaggio sono riservate e ad uso esclusivo del destinatario. Qualora il messaggio in parola Le fosse pervenuto per errore, La preghiamo di eliminarlo senza copiarlo e di non inoltrarlo a terzi, dandocene gentilmente comunicazione. Grazie. Privacy Information - This message, for the Regulation (UE) 2016/679, may contain confidential and/or privileged information. 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