- fca-list - lists.cs.uni-kassel.de

Request for Comments: a repository for formal contexts

by Robert Jäschke

Dear friends of FCA, This mail got longer than anticipated. In short: I propose to create a repository of formal contexts with machine-readable metadata. You can find a initial draft here: https://github.com/fcatools/contexts The long story: Sometimes it would be helpful to have exemplary formal contexts readily available, for example, for illustrational purposes, for testing algorithms, for benchmarking, or for beginners to explore and learn FCA. However, I have not found a comprehensive repository of example formal contexts. I know that Uta Priss has some classic contexts on her web page (https://upriss.github.io/fca/examples.html) and some FCA tools have contexts for unit tests (e.g., https://github.com/tomhanika/conexp-clj/tree/dev/testing-data) but these are neither comprehensive nor easy to find, they have no machine-readable metadata, they are not integrated into FCA tools or libraries, and they are sometimes difficult to cite. What I would like to have for FCA is what popular data science libraries provide. For example, scikit-learn (https://scikit-learn.org/) has some basic datasets (https://scikit-learn.org/stable/datasets/toy_dataset.html) included which can be accessed with just one line of Python code: iris = datasets.load_iris() Similarly, Seaborn's load_dataset() method loads datasets from a git repository (https://github.com/mwaskom/seaborn-data). As there are many frequently-used exemplary formal contexts, I suggest to create a git-based repository which contains such contexts together with machine-readable metadata that describes them. I'd like to follow the KISS principle and not over-engineer the whole thing, that is, 1. Each context is just a file in a git repository (suitable file formats are open for discussion, IMHO at least CTX). 2. The metadata for each context is described in file that is machine-readable and human-editable. My impression is that a stripped-down version of YAML would be sufficient (that is, just hierarchical key-value pairs). An initial draft of such a repository can be found here: https://github.com/fcatools/contexts Using Git(Hub) has some benefits, for example, version control, a workflow for collaboration and contributions (forks, pull requests), a continous integration pipeline for the automatic generation of derivatives (e.g., human-readable documentation, statistics, lattice diagrams), simple programmatic access using HTTP, etc. (I am aware of research data repositories but I think they are not the best choice for what I have in mind. Still, snapshots of the git repo could regularly be published, e.g., on Zenodo, which supports GitHub.) The repository could easily be integrated into FCA workflows, tools, and libraries and could simplify the (re)use of FCA (data). Specifically, I'd like to support maintainers of FCA tools and libraries to integrate access to the repository such that getting a context is as simple as it is with other data in scikit-learn or Seaborn. With a bit more time and effort more would be possible, for example, a browseable repository of contexts like http://konect.cc/ provides for (social) networks. Next steps towards the abovementioned goals would be: 1. gather feedback from the community 2. develop a curation policy and metadata schema 2. collect contexts and metadata 4. reach out to authors of FCA tools and libraries I'd be very glad to get the discussion started and read your comments. Best regards, Robert Jäschke -- Prof. Dr. Robert Jäschke Humboldt-Universität zu Berlin < https://hu.berlin/RJ >>>>>>>>>>><<<<<<<<<<< +49 (0)30 2093-70960 > < https://weltliteratur.net/ >>>>><<<<< https://dev.bibsonomy.org/ >

2 months, 1 week

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Third Call for Papers: Special issue on Ontology Matching and Machine Learning (Semantic Web Journal)

by Cassia TROJAHN

Special issue on Ontology Matching and Machine Learning https://www.semantic-web-journal.net/blog/special-issue-ontology-matching-a… ------------------- This special issue aims to discuss the latest research proposals and on the use of machine learning for ontology matching, data interlinking, and data integration in general. Ontology matching is a key interoperability enabler for the Semantic Web, as well as a useful technique in some classical data integration tasks dealing with the semantic heterogeneity problem. It takes ontologies as input and determines as output an alignment, that is, a set of correspondences between the semantically related entities of those ontologies. These correspondences can be used for various tasks, such as ontology merging, data interlinking, query answering or navigation over knowledge graphs. Thus, matching ontologies enables the knowledge and data expressed with the matched ontologies to interoperate. While early approaches have addressed the use of machine learning, new deep learning and large language models have gained attention in the field, proving new ways of capturing the relationships between the entities of different ontologies. The special issue aims at providing a comprehensive view of the latest research advancements and inspire further research in this evolving area. We welcome original research papers that propose novel techniques, models, and frameworks for ontology matching, data interlink and data integration. ------------------- Themes and Topics ------------------- We are interested in (including but not limited to) the following themes and topics that study the application of deep learning and large language models in general: - Matching and deep learning - Matching and large language models - Learning in instance matching, data interlinking - Large-scale and efficient matching techniques - Matching and neuro-symbolic techniques - Matcher selection, combination and tuning - User involvement - Explanations in matching - Social and collaborative matching - Uncertainty in matching - Expressive alignments - Reasoning with alignments - Alignment coherence and debugging - Matching for emerging applications (e.g., web tables, knowledge graphs) - Benchmarks for machine learning oriented matching ------------------- Deadline ------------------- Submission deadline: 20th February 2024. Papers submitted before the deadline will be reviewed upon receipt. ------------------- Author Guidelines ------------------- We invite full papers, dataset descriptions, application reports and reports on tools and systems. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this special issue. Authors can extend previously published conference or workshop papers; guidelines for this can be found in FAQ 9. Submissions shall be made through the Semantic Web journal website at http://www.semantic-web-journal.net. Prospective authors must take notice of the submission guidelines posted at http://www.semantic-web-journal.net/authors. We welcome any submission type as described http://www.semantic-web-journal.net/authors#types. While there is no upper limit, paper length must be justified by content. Note that you need to request an account on the website for submitting a paper. Please indicate in the cover letter that it is for the "Ontology Matching and Machine Learning" special issue. All manuscripts will be reviewed based on the SWJ open and transparent review policy and will be made available online during the review process. Also note that the Semantic Web journal is open access and all submissions rely on an open and transparent review process (see FAQ 1). Finally please note that submissions must comply with the journal’s Open Science Data requirements, which are detailed in the corresponding blog post. ------------------- Guest Editors The guest editors can be reached at om-ml(a)googlegroups.com . ------------------- Cássia Trojahn, IRIT, France Sven Hertling, University of Mannheim, Germany Huanyu Li, Linköping University, Sweden Oktie Hassanzadeh, IBM Research, USA ------------------- Guest Editorial Board ------------------- Ernesto Jiménez-Ruiz, City, Univeristy of London, UK & SIRIUS, Univeristy of Oslo, Norway Pavel Shvaiko, Trentino Digitale, Italy Jérôme Euzenat, INRIA & Univ. Grenoble Alpes, France Vasilis Efthymiou, Harokopio University of Athens, Greece George Papadakis, National and Kapodistrian University of Athens, Greece Heiko Paulheim, University of Mannheim, Germany Catia Pesquita, Universidade de Lisboa, Portugal Pierre Monnin, Université Côte d’Azur, INRIA, France Alsayed Algergawy, University of Passau, Germany Yuan He, University of Oxford, United Kingdom Jiaoyan Chen, University of Oxford, United Kingdom Zhu Wang, University of Illinois, Chicago, USA Valentina Tamma, University of Liverpool United Kingdom Olivier Teste, Institut de Recherche en Informatique de Toulouse, France

2 months, 2 weeks

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CfP - HHAI 2024 [Extended Deadline] - The third International Conference on Hybrid Human-Artificial Intelligence

by Grootjen, Jesse

* We apologize if you receive multiple copies of this email * Call for Participation: HHAI2024 – The third International Conference on Hybrid Human-Artificial Intelligence June 10-14, 2024, Malmö, Sweden Call for Contributions to the Doctoral Consortium In this message, we shortened each call to their essentials – the full text of each call is available on the website: https://hhai-conference.org/2024/ The HHAI 2024 Doctoral Consortium (DC) will take place as part of the 3rd International Conference on Hybrid Human-Artificial Intelligence in June 2024, Malmö, Sweden. This forum will provide early as well as middle/late-stage PhD students in the field of Hybrid Intelligence focusing on the study of Artificial intelligence systems that cooperate synergistically, proactively and purposefully with humans, amplifying instead of replacing human intelligence. The Doctoral Consortium will take place in person at the HHAI 2024 conference. Important Dates All deadlines are 23:59 AoE (anywhere on Earth). - Submission Deadline: February 12th, 2024 - Reviews Released: March 18th, 2024 - Camera-ready Papers Due: April 18th, 2024 - Doctoral Consortium: June 11th, 2024 Proposals should be submitted via Easychair: https://easychair.org/conferences/?conf=hhai2024 Location HHAI 2024 will be an in-person, single-track conference, held in Malmö, Sweden on June 10-14, 2024. More information on the venue as well as travel information can be found on the website: https://hhai-conference.org/2024/ Contact information Conference chairs: Frank Dignum (Umeå University, SE), Fabian Lorig (Malmö University, SE), Jason Tucker (Malmö University, SE), and Adam Dahlgren Lindström (Umeå University, SE). Doctoral Consortium chairs: Passant El.Agroudy (DFKI, DE), Michiel van der Meer (Leiden University, NL) and Harko Verhagen (Stockholm University, SE) For questions, you can reach the doctoral consortium chairs at dc(a)hhai-conference.org<mailto:dc@hhai-conference.org> Kind regards, Julian Rasch & Jesse Grootjen Publicity and Social Media Chairs HHAI 2024 https://www.hhai-conference.org/

2 months, 2 weeks

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Text2Story@ECIR'24 Last Call for Papers

by Hugo Oliveira Sousa

*** Apologies for cross-posting *** ++ LAST CALL FOR PAPERS ++ **************************************************************************** Seventh International Workshop on Narrative Extraction from Texts (Text2Story'24) Held in conjunction with the 46th European Conference on Information Retrieval (ECIR'24) March 24th, 2024 – Glasgow, Scotland Website: https://text2story24.inesctec.pt<https://text2story24.inesctec.pt/> **************************************************************************** ++ Important Dates ++ - Submission Deadline: February 7th, 2024 - Acceptance Notification: March 1st, 2024 - Camera-ready copies: March 15th, 2024 - Workshop: March 24th, 2024 ++ Overview ++ Over these past years, significant breakthroughs, led by Transformers and Large Language Models (LLMs), have been made in understanding natural language text. However, the ability to capture, represent, and analyze contextual nuances in longer texts is still an elusive goal, let alone the understanding of consistent fine-grained narrative structures in text. In the seventh edition of the Text2Story workshop, we aim to bring to the forefront the challenges involved in understanding the structure of narratives and in incorporating their representation in well-established frameworks, as well as in modern architectures (e.g., transformers) and AI-powered language models (e.g, chatGPT) which are now common and form the backbone of almost every IR and NLP application. It is hoped that the workshop will provide a common forum to consolidate the multi-disciplinary efforts and foster discussions to identify the wide-ranging issues related to the narrative extraction task. ++ List of Topics ++ Research works submitted to the workshop should foster the scientific advance on all aspects of storyline generation and understanding from texts including but not limited to narrative information extraction aspects, narratives representation, knowledge extraction, ethics and bias in narratives, datasets and evaluation protocols and narrative applications such as visualization of narratives, multi-modal aspects, Q&A, etc. To this regard, we encourage the submission of high-quality and original submissions covering the following topics: Information Extraction Aspects * Temporal Relation Identification * Temporal Reasoning and Ordering of Events * Causal Relation Extraction and Arrangement * Big Data Applied to Narrative Extraction Narrative Representation * Annotation protocols * Narrative Representation Models * Lexical, Syntactic, and Semantic Ambiguity in Narrative Representation Narrative Analysis and Generation * Argumentation Analysis * Language Models and Transfer Learning in Narrative Analysis * Narrative Analysis in Low-resource Languages * Multilinguality: Multilingual and Cross-lingual Narrative Analysis * Comprehension of Generated Narratives * Story Evolution and Shift Detection * Automatic Timeline Generation Datasets and Evaluation Protocol * Evaluation Methodologies for Narrative Extraction * Annotated datasets * Narrative Resources Ethics and Bias in Narratives * Bias Detection and Removal in Generated Stories * Ethical and Fair Narrative Generation * Misinformation and Fact Checking Narrative Applications * Narrative-focused Search in Text Collections * Narrative Summarization * Narrative Q&A * Multi-modal Narrative Summarization * Sentiment and Opinion Detection in Narratives * Social Media Narratives * Narrative Simplification * Personalization and Recommendation of Narratives * Storyline Visualization ++ Dataset ++ We challenge the interested researchers to consider submitting a paper that makes use of the tls-covid19 dataset - published at ECIR'21 - under the scope and purposes of the text2story workshop. tls-covid19 consists of a number of curated topics related to the Covid-19 outbreak, with associated news articles from Portuguese and English news outlets and their respective reference timelines as gold-standard. While it was designed to support timeline summarization research tasks it can also be used for other tasks (e.g., Q&A), especially when combined with Large Language Models (LLMs) like ChatGPT. A script to reconstruct and expand the dataset is available at https://github.com/LIAAD/tls-covid19. The article itself is available at this link: https://link.springer.com/chapter/10.1007/978-3-030-72113-8_33 ++ Submission Guidelines ++ We solicit the following types of contributions: * Full papers up to 8 pages + references Original and high-quality unpublished contributions to the theory and practical aspects of the narrative extraction task. Full papers should introduce existing approaches, describe the methodology and the experiments conducted in detail. Negative result papers to highlight tested hypotheses that did not get the expected outcome are also welcomed. * Short papers up to 5 pages + references Unpublished short papers describing work in progress; position papers introducing a new point of view, a research vision or a reasoned opinion on the workshop topics; and dissemination papers describing project ideas, ongoing research lines, case studies or summarized versions of previously published papers in high-quality conferences/journals that is worthwhile sharing with the Text2Story community, but where novelty is not a fundamental issue. * Demos | Resource Papers up to 5 pages + references Unpublished papers presenting research/industrial demos; papers describing important resources (datasets or software packages) to the text2story community; Submissions will be peer-reviewed by at least two members of the programme committee. The accepted papers will appear in the proceedings published at CEUR workshop proceedings (indexed in Scopus and DBLP) as long as they don't conflict with previous publication rights. ++ Workshop Format ++ Participants of accepted papers will be given 15 minutes for oral presentations. ++ Invited Speakers ++ Homo narrans: From Information to Narratives Jochen L. Leidner<https://www.coburg-university.de/about-us/faculties/faculty-of-business-and…>, Coburg University of Applied Sciences, Germany Abstract: Humans are curious creatures, equipped with a sense of (and desire for) finding meaning in their environment. They are predisposed to identify patterns, real and spurious, in the world they live in, and above anything else, they understand the world in terms of narratives. In this talk, we will explore a set of questions about narratives: what is a narrative made up of? What signals from textual prose tell us what the narrative is? What about signals from structured data that imply a particular narrative? What is the essence of a story? How can narrative information be extracted and presented? Open source intelligence analysts and investigative reporters alike are hunting for the story, the narrative, behind the petabyte intercepts or terabyte leaks. The more data we gather or have available, the stronger will be our thirst to distill meaningful stories from it. Bio: Professor Jochen L. Leidner MA MPhil PhD FRGS is the Research Professor for Explainable and Responsible Artificial Intelligence in Insurance at Coburg University of Applied Sciences and Arts, Germany, where he leads the Information Access Research Group, a Visiting Professor of Data Analytics in the Department of Computer Science, University of Sheffield and founder and CEO of the consultancy KnowledgeSpaces. He is also a Fellow of the Royal Geographical Society. Dr. Leidner's experience includes positions as Director of Research at Thomson Reuters and Refinitiv in London, where he headed its R&D team (2013-2022). He has built up research and innovation teams. He was also the Royal Academy of Engineering Visiting Professor of Data Analytics at the Department of Computer Science. His background includes a Master's in computational linguistics, English and computer science (University of Erlangen-Nuremberg), a Master's in Computer Speech, Text and Internet Technology (University of Cambridge) and a PhD in Informatics (University of Edinburgh), which won the first ACM SIGIR Doctoral Consortium Award. He is a scientific expert for the European Commission (FP7, H2020, Horizon Europe) and other funding bodies in Germany, Austria, the UK and the USA. He also is a past chair of the Microsoft-BCS/BCS IRSG Karen Sparck Jones award. Professor Leidner is an author or co-author of several dozen peer-reviewed publications (including one best paper award), has authored or co-edited two books and holds several patents in the areas of information retrieval, natural language processing, and mobile computing. He has been twice winner of the Thomson Reuters inventor of the year award for the best patent application, and is the past received of a Royal Society of Edinburgh Enterprise Fellowship in Electronic Markets. Visual Storytelling with Question-Answer Plans Mirella Lapata, University of Edinburgh, Scotland Abstract: Visual storytelling aims to generate compelling narratives from image sequences. Existing models often focus on enhancing the representation of the image sequence, e.g., with external knowledge sources or advanced graph structures. Despite recent progress, the stories are often repetitive, illogical, and lacking in detail. To mitigate these issues, we present a novel framework which integrates visual representations with pretrained language models and planning. Our model translates the image sequence into a visual prefix, a sequence of continuous embeddings which language models can interpret. It also leverages a sequence of question-answer pairs as a blueprint plan for selecting salient visual concepts and determining how they should be assembled into a narrative. Automatic and human evaluation on the VIST benchmark (Huang et al., 2016) demonstrates that blueprint-based models generate stories that are more coherent, interesting, and natural compared to competitive baselines and state-of-the-art systems. Bio: Professor Mirella Lapata is a faculty member in the School of Informatics at the University of Edinburgh. She is affiliated with the Institute for Communicating and Collaborative Systems and the Edinburgh Natural Language Processing Group. Her research centers on computational models for the representation, extraction, and generation of semantic information from structured and unstructured data. This encompasses various modalities, including text, images, video, and large-scale knowledge bases. Prof. Lapata has contributed to diverse applied Natural Language Processing (NLP) tasks, such as semantic parsing, semantic role labeling, discourse coherence, summarization, text simplification, concept-to-text generation, and question answering. Using primarily probabilistic generative models, she has employed computational models to investigate aspects of human cognition, including learning concepts, judging similarity, forming perceptual representations, and learning word meanings. The overarching objective of her research is to empower computers to comprehend requests, execute actions based on them, process and aggregate large datasets, and convey information derived from them. Central to these endeavors are models designed for extracting and representing meaning from natural language text, internally storing meanings, and leveraging stored meanings to deduce further consequences. ++ Organizing committee ++ Ricardo Campos (INESC TEC; University of Beira Interior, Covilhã, Portugal) Alípio M. Jorge (INESC TEC; University of Porto, Portugal) Adam Jatowt (University of Innsbruck, Austria) Sumit Bhatia (Media and Data Science Research Lab, Adobe) Marina Litvak (Shamoon Academic College of Engineering, Israel) ++ Proceedings Chair ++ João Paulo Cordeiro (INESC TEC & Universidade da Beira do Interior) Conceição Rocha (INESC TEC) ++ Web and Dissemination Chair ++ Hugo Sousa (INESC TEC & University of Porto) Behrooz Mansouri (Rochester Institute of Technology) ++ Program Committee ++ Álvaro Figueira (INESC TEC & University of Porto) Andreas Spitz (University of Konstanz) Antoine Doucet (Université de La Rochelle) António Horta Branco (University of Lisbon) Anubhav Jangra (IIT Patna, Japan) Arian Pasquali (Faktion AI) Bart Gajderowicz (University of Toronto) Begoña Altuna (Universidad del País Vasco) Behrooz Mansouri (Rochester Institute of Technology) Brenda Santana (Federal University of Rio Grande do Sul) Bruno Martins (IST & INESC-ID, University of Lisbon) Brucce dos Santos (Computational Intelligence Laboratory (LABIC) - ICMC/USP) David Semedo (Universidade NOVA de Lisboa) Deya Banisakher (Florida International University) Dhruv Gupta (Norwegian University of Science and Technology) Evelin Amorim (INESC TEC) Henrique Lopes Cardoso (LIACC & University of Porto) Ignatius Ezeani (Lancaster University) Irina Rabaev (Shamoon College of Engineering) Ismail Altingovde (Middle East Technical University) João Paulo Cordeiro (INESC TEC & University of Beira Interior) Liana Ermakova (HCTI, Université de Bretagne Occidentale) Luca Cagliero (Politecnico di Torino) Ludovic Moncla (INSA Lyon) Luis Filipe Cunha (INESC TEC & University of Minho) Marc Finlayson (Florida International University) Marc Spaniol (Université de Caen Normandie) Mariana Caravanti (Computational Intelligence Laboratory (LABIC) - ICMC/USP) Moreno La Quatra (Kore University of Enna) Natalia Vanetik (Sami Shamoon College of Engineering) Nuno Guimarães (INESC TEC & University of Porto) Pablo Gervás (Universidad Complutense de Madrid) Paulo Quaresma (Universidade de Évora) Purificação Silvano (CLUP & University of Porto) Ross Purves (University of Zurich) Satya Almasian (Heidelberg University) Sérgio Nunes (INESC TEC & University of Porto) Sriharsh Bhyravajjula (University of Washington) Udo Kruschwitz (University of Regensburg) Valentina Bartalesi (ISTI-CNR, Italy) ++ Contacts ++ Website: https://text2story24.inesctec.pt<https://text2story24.inesctec.pt/> For general inquiries regarding the workshop, reach the organizers at: text2story2024(a)easychair.org<mailto:text2story2024@easychair.org>

3 months

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CfP - HHAI 2024 [Extended Deadline] - The third International Conference on Hybrid Human-Artificial Intelligence

by Grootjen, Jesse

* We apologize if you receive multiple copies of this email * Call for Participation: HHAI2024 – The third International Conference on Hybrid Human-Artificial Intelligence June 10-14, 2024, Malmö, Sweden Call for Workshop and Tutorial Proposals & Doctoral Consortium In this message, we shortened each call to their essentials – the full text of each call is available on the website: https://hhai-conference.org/2024/ Call for Workshop and Tutorial Proposals We invite proposals for two-day, full-day and half-day workshops at HHAI 2024. We also invite tutorials to run alongside the workshops. The workshops and tutorials will form part of the first edition of the HHAI Summer School. The HHAI 2024 workshops and tutorials provide a platform for discussing a topic related to Hybrid Human-Artificial Intelligence with an audience specifically interested in that topic in an informal setting (compared to the main conference). We invite submissions for events that foster cross-disciplinary interaction, scientific discourse, and creative and critical reflection, rather than just being mini-conferences. We offer organizers flexibility on formats that best suit the goals of their event. We also welcome submissions from research communities that may not be prominently featured in AI events and conferences. Important Dates - Workshop and tutorial proposals: January 31, 2024 February 9, 2024 - Proposal acceptance notification: February 7, 2024 February 14, 2024 - Deadline for announcing the Call for Contributions to the workshops: February 14, 2024 February 21, 2024 - Recommended deadline for submissions to the workshops: April 10, 2024 - Recommended deadline for notifications on the submissions: May 2, 2024 - Workshops and tutorials at HHAI2024: June 10-11, 2024 Proposals should be submitted via Easychair: https://easychair.org/conferences/?conf=hhai2024 Doctoral Consortium Call for Contributions The HHAI 2024 Doctoral Consortium (DC) will take place as part of the 3rd International Conference on Hybrid Human-Artificial Intelligence in June 2024, Malmö, Sweden. This forum will provide early as well as middle/late-stage PhD students in the field of Hybrid Intelligence focusing on the study of Artificial intelligence systems that cooperate synergistically, proactively and purposefully with humans, amplifying instead of replacing human intelligence. The Doctoral Consortium will take place in person at the HHAI 2024 conference. Important Dates All deadlines are 23:59 AoE (anywhere on Earth). - Submission Deadline: February 12th, 2024 - Reviews Released: March 18th, 2024 - Camera-ready Papers Due: April 18th, 2024 - Doctoral Consortium: June 11th, 2024 Proposals should be submitted via Easychair: https://easychair.org/conferences/?conf=hhai2024 Location HHAI 2024 will be an in-person, single-track conference, held in Malmö, Sweden on June 10-14, 2024. More information on the venue as well as travel information can be found on the website: https://hhai-conference.org/2024/ Contact information Conference chairs: Frank Dignum (Umeå University, SE), Fabian Lorig (Malmö University, SE), Jason Tucker (Malmö University, SE), and Adam Dahlgren Lindström (Umeå University, SE). Program chairs: Pradeep Murukannaiah (TU Delft, NL), Andreas Theodorou (Umeå University, SE), Pinar Yolum (Utrecht University, NL). Workshop chairs: Petter Ericson (Umeå University, SE), Nina Khairova (Umeå University, SE), Marina de Vos (University of Bath, UK) Doctoral Consortium chairs: Passant El.Agroudy (DFKI, DE), Michiel van der Meer (Leiden University, NL) and Harko Verhagen (Stockholm University, SE) For questions, you can reach the program chairs at program(a)hhai-conference.org<mailto:program@hhai-conference.org>, the workshop chairs at workshop(a)hhai-conference.org<mailto:workshop@hhai-conference.org> and the doctoral consortium chars at dc(a)hhai-conference.org<mailto:dc@hhai-conference.org> Kind regards, Julian Rasch & Jesse Grootjen Publicity and Social Media Chairs HHAI 2024 https://www.hhai-conference.org/

3 months

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1st International Joint Conference on Conceptual Knowledge Structures - 2nd Call for Papers

by Sebastien Ferre

*** 2nd Call for Papers *** CONCEPTS 2024 1st International Joint Conference on Conceptual Knowledge Structures 28th Intl. Conf. on Conceptual Structures (ICCS) 18th Intl. Conf. on Formal Concept Analysis (ICFCA) 17th Intl. Conf. on Concept Lattices and their Applications (CLA) September 9–13 2024, Cádiz, Spain Website: https://concepts2024.uca.es <https://concepts2024.uca.es> Email contact address: concepts24(a)lists.cs.uni-kassel.de <mailto:concepts24@lists.cs.uni-kassel.de> The 1st International Joint Conference on Conceptual Knowledge Structures (CONCEPTS) 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. This new conference aims to continue the tradition and standards of previous conferences and become a key annual meeting to take along all members of the three communities of CLA, ICCS, and ICFCA and to keep abreast of the advances and new challenges in the field. Main topics include but are not limited to: - Formal concept analysis: concept lattices, implications, algorithms and computational complexity - Conceptual graphs, graph-based models for human reasoning - Knowledge spaces and learning spaces - Ontologies, semantic web, knowledge graphs - Conceptual structures in natural language processing and linguistics - Conceptual knowledge acquisition and management - Conceptual knowledge discovery, data analysis, and visualization - Probabilistic approaches to conceptual knowledge representation and knowledge discovery - Approximation techniques in application to conceptual structures - Bridging conceptual structures to information sciences, artificial intelligence, data mining, machine learning, information retrieval, database theory, software engineering, and other areas of computer science - Understanding real-world data and modeling real-world phenomena with conceptual structures *Submission details:* Submissions are invited on significant, original (previously unpublished) research on the topics of the conference. All accepted submissions will be refereed, by following three different modalities: * journal track papers, up to 26 pages, to be published in a special issue of the 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, 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 6, 2024 - Paper reviews sent to authors: May 3, 2024 - Revised submission: June 3, 2024 - Notification of acceptance: June 30, 2024 Manuscripts must be submitted via the International Journal of Approximate Reasoning online submission system (Editorial Manager®): https://www2.cloud.editorialmanager.com/ija/default2.aspx <https://www2.cloud.editorialmanager.com/ija/default2.aspx>. Please select the article type “*VSI: CONCEPTS 2024*” when submitting your manuscript online. Please refer to the Guide for Authors to prepare your manuscript: https://www.elsevier.com/journals/international-journal-of-approximate-reas… <https://www.elsevier.com/journals/international-journal-of-approximate-reas…>. See also LaTeX instructions: https://www.elsevier.com/researcher/author/policies-and-guidelines/latex-in… <https://www.elsevier.com/researcher/author/policies-and-guidelines/latex-in…>. /***Regular and short papers***/ - Abstract submission: March 18, 2024 - Full paper submission: March 25, 2024 - Notification of acceptance: May 15, 2024 - Camera-ready papers due: May 30, 2024 Submission link: https://equinocs.springernature.com/service/CONCEPTS2024 <https://equinocs.springernature.com/service/CONCEPTS2024>. Please select the appropriate category for your submitted manuscript, 'regular paper' or 'short paper'. Please visit the page 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:_ Jesús Medina, University of Cádiz, Spain _Program Chairs:_ Inma P. Cabrera, University of Málaga, Spain Sébastien Ferré, University of Rennes, France Sergei Obiedkov, TU Dresden, Germany _Local organizer Committee:_ María José Benítez Caballero, University of Cádiz, Spain Fernando Chacón-Gómez, University of Cádiz, Spain Samuel José Molina Ruiz, University of Cádiz, Spain Francisco José Ocaña Alcázar, University of Cádiz, Spain _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

3 months, 1 week

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Warning: Predatory conference on "FCA"

by Gerd Stumme

Dear all, there is currently a call on the web for "ICFCA 2024: 18. International Conference on Formal Concept Analysis", organized by the "World Academy of Science, Engineering and Technology" [1] in April 2024 in New York. Please note that this is a predatory conference! For not promoting this fake event further, I refrain from adding a link. Wikipedia is describing the predatory nature of this organisation. Please note that this year, ICFCA is joining with CLA and ICCS, as previously announced. The joint conference, CONCEPTS 2024, is going to be held at Cádiz, Spain on September 9-13. Deadlines are March 6 for the journal track and March 18 for the proceedings track. Details can be found at https://concepts2024.uca.es/ Best regards, Gerd -- Prof. Dr. Gerd Stumme, Hertie Chair of Knowledge & Data Engineering & Research Center for Information System Design (ITeG) & International Center for Higher Education Research (INCHER), University of Kassel & Research Center L3S & The Hessian Center for Artificial Intelligence (hessian.AI) http://www.kde.cs.uni-kassel.de, Tel. +49 561/804-6251

3 months, 2 weeks

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First Call for papers: Special issue on Ontology Matching and Machine Learning (Semantic Web Journal)

by Cassia TROJAHN

Special issue on Ontology Matching and Machine Learning https://www.semantic-web-journal.net/blog/special-issue-ontology-matching-a… ------------------- This special issue aims to discuss the latest research proposals and on the use of machine learning for ontology matching, data interlinking, and data integration in general. Ontology matching is a key interoperability enabler for the Semantic Web, as well as a useful technique in some classical data integration tasks dealing with the semantic heterogeneity problem. It takes ontologies as input and determines as output an alignment, that is, a set of correspondences between the semantically related entities of those ontologies. These correspondences can be used for various tasks, such as ontology merging, data interlinking, query answering or navigation over knowledge graphs. Thus, matching ontologies enables the knowledge and data expressed with the matched ontologies to interoperate. While early approaches have addressed the use of machine learning, new deep learning and large language models have gained attention in the field, proving new ways of capturing the relationships between the entities of different ontologies. The special issue aims at providing a comprehensive view of the latest research advancements and inspire further research in this evolving area. We welcome original research papers that propose novel techniques, models, and frameworks for ontology matching, data interlink and data integration. ------------------- Themes and Topics ------------------- We are interested in (including but not limited to) the following themes and topics that study the application of deep learning and large langage models in general: - Matching and deep learning - Matching and large language models - Learning in instance matching, data interlinking - Large-scale and efficient matching techniques - Matching and neuro-symbolic techniques - Matcher selection, combination and tuning - User involvement - Explanations in matching - Social and collaborative matching - Uncertainty in matching - Expressive alignments - Reasoning with alignments - Alignment coherence and debugging - Matching for emerging applications (e.g., web tables, knowledge graphs) - Benchmarks for machine learning oriented matching ------------------- Deadline ------------------- Submission deadline: 20th February 2024. Papers submitted before the deadline will be reviewed upon receipt. ------------------- Author Guidelines ------------------- We invite full papers, dataset descriptions, application reports and reports on tools and systems. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this special issue. Authors can extend previously published conference or workshop papers; guidelines for this can be found in FAQ 9. Submissions shall be made through the Semantic Web journal website at http://www.semantic-web-journal.net. Prospective authors must take notice of the submission guidelines posted at http://www.semantic-web-journal.net/authors. We welcome any submission type as described http://www.semantic-web-journal.net/authors#types. While there is no upper limit, paper length must be justified by content. Note that you need to request an account on the website for submitting a paper. Please indicate in the cover letter that it is for the "Ontology Matching and Machine Learning" special issue. All manuscripts will be reviewed based on the SWJ open and transparent review policy and will be made available online during the review process. Also note that the Semantic Web journal is open access and all submissions rely on an open and transparent review process (see FAQ 1). Finally please note that submissions must comply with the journal’s Open Science Data requirements, which are detailed in the corresponding blog post. ------------------- Guest Editors The guest editors can be reached at om-ml(a)googlegroups.com . ------------------- Cássia Trojahn, IRIT, France Sven Hertling, University of Mannheim, Germany Huanyu Li, Linköping University, Sweden Oktie Hassanzadeh, IBM Research, USA ------------------- Guest Editorial Board ------------------- Ernesto Jiménez-Ruiz, City, University of London, UK & SIRIUS, University of Oslo, Norway Pavel Shvaiko, Trentino Digitale, Italy Jérôme Euzenat, INRIA & Univ. Grenoble Alpes, France TO BE COMPLETED

3 months, 3 weeks

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IAOA Honorary Fellowship Award - Call for Nominations by Jan 21, 2024

by Frank Loebe

[forwarded on behalf of Oliver Kutz] == Award Announcement and Call for Nominations == The IAOA [1] has established an award of honorary fellowships [2] in order to recognise distinguished scholars in the field of applied ontology. IAOA Fellows will have contributed significantly and in a sustained manner to the field of applied ontology, for example by outstanding scientific achievements, which often goes hand-in-hand with their strong dedication and service to the community. Their selection is subject to an annual process based on nominations from the community. For 2024, we solicit nominations by January 21, 2024 (Sunday, UTC-12). Please send nominations to [3] info(a)iaoa.org. Complete details on the process are specified in the IAOA's Fellowship Procedure [4], an excerpt of which describing the nomination requirements is copied below. The 2024 selection committee consists of - João Paulo A. Almeida, Federal University of Espirito Santo (UFES), Vitoria, Brazil - Nicola Guarino, Laboratory for Applied Ontology (LOA), Trento, Italy - Oliver Kutz, Free University of Bozen-Bolzano, Italy - Deborah McGuinness, Rensselaer Polytechnic Institute, New York, USA - Laure Vieu, Toulouse Institute for Computer Science Research (IRIT), France We look forward to each nomination, with many thanks in advance for the effort! Best regards, Oliver Kutz President, IAOA --- < excerpt from [4] > To nominate a person, a nominator sends a message to the committee that summarizes the main contributions of the nominee to applied ontology and argues why the nominee should be selected. The nomination should be seconded by at least one supporter. Among the nominator and the supporter(s), at least one should be an IAOA member. Self nominations are not allowed. A nominee cannot be part of the selection committee. If that happens, the nominee will be given the option to reject the nomination or withdraw from the selection committee. </ excerpt > --- [1] International Association for Ontology and its Applications (IAOA) https://iaoa.org [2] IAOA Fellowship (web page) https://iaoa.org/index.php/organization/fellows/ [3] IAOA contact mail address, to be used for nominations info(a)iaoa.org [4] IAOA Fellowship Procedure https://iaoa.org/wp-content/uploads/2023/12/IAOA-Fellow-Procedure.pdf

3 months, 3 weeks

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2nd CfP - HHAI 2024 - The third International Conference on Hybrid Human-Artificial Intelligence

by Grootjen, Jesse

Call for Participation: HHAI2024 – The third International Conference on Hybrid Human-Artificial Intelligence June 10-14, 2024, Malmö, Sweden Call for Papers & Call for Workshop and Tutorial Proposals In this message, we shortened each call to their essentials – the full text of each call is available on the website: https://hhai-conference.org/2024/ Hybrid Human-Artificial Intelligence (HHAI) is an international conference series that focuses on the study of Artificial Intelligence systems that cooperate synergistically, proactively and purposefully with humans, amplifying instead of replacing human intelligence. HHAI aims for AI systems that work together with humans, emphasizing the need for adaptive, collaborative, responsible, interactive and human-centered intelligent systems. HHAI systems leverage human strengths and compensate for human weaknesses, while taking into account social, ethical and legal considerations. The HHAI field is driven by developments in AI, but it also requires fundamentally new approaches and solutions. Thus, we encourage collaborations across research domains such as AI, HCI, cognitive and social sciences, philosophy & ethics, complex systems, and others. In this third international conference, we invite scholars from these fields to submit their best original – new as well as in progress – works, and visionary ideas on Hybrid Human-Artificial Intelligence. Call for Papers (Main track) Important dates - Abstract submission: January 26, 2024 - Paper submission: February 2, 2024 - Acceptance notification: March 29, 2024 - Camera-ready version: April 12, 2024 Topics We invite research on different challenges in Hybrid Human-Artificial Intelligence. The following list of topics is illustrative, not exhaustive: - Human-AI interaction and collaboration - Adaptive human-AI co-learning and co-creation - Learning, reasoning and planning with humans and machines in the loop - User modeling and personalisation - Integration of learning and reasoning - Transparent, explainable, and accountable AI - Fair, ethical, responsible, and trustworthy AI - Societal awareness of AI - Multimodal machine perception of real world settings - Social signal processing - Representations learning for Communicative or Collaborative AI - Symbolic and narrative-based representations for human-centric AI - Role of Design and Compositionality of AI systems in Interpretable / Collaborative AI We welcome contributions about all types of technology, from robots and conversational agents to multi-agent systems and machine learning models. Paper types In this conference, we wish to stimulate the exchange of novel ideas and interdisciplinary perspectives. To do this, we will accept three different types of papers: - Full papers present original, impactful work (12 pages excl. references) - Blue sky papers present visionary ideas to stimulate the research community (8 pages excl. references) - Working papers present work in progress (8 pages excl.references) Accepted full papers and Blue sky papers will be published in the Proceedings of the Third International Conference on Hybrid Human-Machine Intelligence, in the Frontiers of AI series by IOS Press. Working papers can be included in these proceedings, unless the authors request the paper to remain unpublished. Work should be submitted in PDF format via Easychair: https://easychair.org/conferences/?conf=hhai2024 Call for Workshop and Tutorial Proposals We invite proposals for two-day, full-day and half-day workshops at HHAI 2024. We also invite tutorials to run alongside the workshops. The workshops and tutorials will form part of the first edition of the HHAI Summer School. The HHAI 2024 workshops and tutorials provide a platform for discussing a topic related to Hybrid Human-Artificial Intelligence with an audience specifically interested in that topic in an informal setting (compared to the main conference). We invite submissions for events that foster cross-disciplinary interaction, scientific discourse, and creative and critical reflection, rather than just being mini-conferences. We offer organizers flexibility on formats that best suit the goals of their event. We also welcome submissions from research communities that may not be prominently featured in AI events and conferences. Important Dates - Workshop and tutorial proposals: January 31, 2024 - Proposal acceptance notification: February 7, 2024 - Deadline for announcing the Call for Contributions to the workshops: February 14, 2024 - Recommended deadline for submissions to the workshops: April 10, 2024 - Recommended deadline for notifications on the submissions: May 2, 2024 - Workshops and tutorials at HHAI2024: June 10-11, 2024 Proposals should be submitted via Easychair: https://easychair.org/conferences/?conf=hhai2024 Location HHAI 2024 will be an in-person, single-track conference, held in Malmö, Sweden on June 10-14, 2024. More information on the venue as well as travel information can be found on the website: https://hhai-conference.org/2024/ Contact information Conference chairs: Frank Dignum (Umeå University, SE), Fabian Lorig (Malmö University, SE), Jason Tucker (Malmö University, SE), and Adam Dahlgren Lindström (Umeå University, SE). Program chairs: Pradeep Murukannaiah (TU Delft, NL), Andreas Theodorou (Umeå University, SE), Pinar Yolum (Utrecht University, NL). Workshop chairs: Petter Ericson (Umeå University, SE), Nina Khairova (Umeå University, SE), Marina de Vos (University of Bath, UK) For questions, you can reach the program chairs at program(a)hhai-conference.org<mailto:program@hhai-conference.org> and the workshop chairs at workshop(a)hhai-conference.org<mailto:workshop@hhai-conference.org> Kind regards, Julian Rasch & Jesse Grootjen Publicity and Social Media Chairs HHAI 2024 https://www.hhai-conference.org/

3 months, 3 weeks

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2021