May 2022 - fca-list - lists.cs.uni-kassel.de

2nd Call For Participation - CLA 2022: The 16th International Conference on Concept Lattices and Their Applications

by Ben Yahia Sadok

The 16th International Conference on Concept Lattices and Their Applications June 20–22, 2022. Conference venue: Tallinnk SPA hotel ( Tallinn, Estonia) (https://www.tallinkhotels.com/tallink-spa-conference-hotel) [ https://cs.ttu.ee/events/cla2020/ | https://cs.ttu.ee/events/cla2022/ ] Invited speakers: 1. [ https://cs.ttu.ee/events/cla2022/?page=invited#Tarmo%20Uustalu | Tarmo Uustalu (Reykjavik University, Iceland / Tallinn University of Technology, Estonia) ] 2. [ https://ai.ugent.be/people/BernardDeBaets.en.html | Bernard De Baets ] (Ghent University, Belgium): 3. John F. Sowa ( Kyndi, Inc., San Mateo, CA, USA ): 4. [ https://www.ksi.mff.cuni.cz/~vojtas/ | Peter Vojtáš ] ( [ https://www.mff.cuni.cz/en | Faculty of Mathematics and Physics ] , [ https://cuni.cz/UKEN-1.html | Charles University): ] 5. [ https://sites.google.com/site/boualembenatallahwebsite/ | Boualem Benatallah ] (DCU, Ireland ): Tutorial M ANAGING AND LINKING DATA WITH KG USING [ http://poolparty.biz/ | PP SEMANTIC SUITE ] (HTTPS://CS.TTU.EE/EVENTS/CLA2022/?PAGE=TUTORIAL) - Workshop ETAFCA'2022 - Existing Tools and Applications for Formal Concept Analysis ( https://cs.ttu.ee/events/etafca-2022/ ) . . Accepted papers https://cs.ttu.ee/events/cla2022/?page=papers Prof. Dr. Sadok BEN YAHIA Department of Software Science [GSM: +372 53 653258] Tallinn University of Technology Akadeemia tee 15a, room 649 Tallinn 12618, Estonia

2 years, 1 month

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FCA4AI Workshop: deadline extension!

by Amedeo Napoli

Sorry for duplicates... ------------------------------------------------------------------------------------------------------------------- -- FCA4AI (Tenth Edition) -- ``What can FCA do for Artificial Intelligence?'' co-located with IJCAI-ECAI 2022, Vienna, Austria July 23 or 24 2022 http://www.fca4ai.hse.ru/2022 ------------------------------------------------------------------------------------------------------------------- General Information. The preceding editions of the FCA4AI Workshop (from ECAI 2012 until IJCAI 2021) showed that many researchers working in Artificial Intelligence are indeed interested by powerful techniques for classification and data mining provided by Formal Concept Analysis. Again, we have the chance to organize the 10th edition of the workshop in Vienna, co-located with the IJCAI-ECAI 2022 Conference. 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... 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... - By contrast, how the current developments in AI can be integrated within FCA to help AI researchers solve complex problems in their domain, - Which role can be played by FCA 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. - Practical applications in agronomy, astronomy, biology, chemistry, finance, manufacturing, medicine... The workshop will include time for audience discussion aimed at better understanding of of the issues, challenges, and ideas being presented. IMPORTANT DATES: Submission deadline: June 06 2022 Notification to authors: July 04 2022 Final version: July 14 2022 Workshop: July 23 or 24 2022 SUBMISSION DETAILS: The workshop welcomes submissions in pdf format in Springer's LNCS style. Submissions can be: - technical papers not exceeding 12 pages, - system descriptions or position papers on work in progress not exceeding 6 pages. Submissions are via EasyChair at https://easychair.org/conferences/?conf=fca4ai2022 The workshop proceedings will be published as CEUR proceedings (see preceding editions in CEUR Proceedings 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) ------------------------------------------------------------------------------------------------------------------- -------------------------------------------------------------------------------------------------------------------

2 years, 2 months

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[KaRS 2022] First CfP: 4th Knowledge-aware and Conversational Recommender Systems Workshop 2022 @ ACM RecSys

by Vito Walter Anelli

Call for Papers Fourth Workshop on Knowledge-aware and Conversational Recommender Systems (KaRS 2022) https://kars-workshop.github.io/2022/ Sep. 18th - Sep. 23rd, 2022, Seattle, WA, USA Submission deadline: August 5th, 2022, AoE [SCOPE] We are pleased to invite you to contribute to the Fourth Workshop on Knowledge-aware and Conversational Recommender Systems held in conjunction with the ACM International Conference on Recommender Systems (RecSys 2022), Seattle, WA, USA, from September the 18th to September the 23rd, 2022. In the last few years, a renewed interest of the research community on conversational recommender systems (CRSs) is emerging. This is probably due to the great diffusion of Digital Assistants (DAs) such as Amazon Alexa, Siri, or Google Assistant that are revolutionizing the way users interact with machines. DAs allow users to execute a wide range of actions through an interaction mostly based on natural language messages. However, although DAs are able to complete tasks such as sending texts, making phone calls, or playing songs, they are still at an early stage on offering recommendation capabilities by using the conversational paradigm. In addition, we have been witnessing the advent of more and more precise and powerful recommendation algorithms and techniques able to effectively assess users' tastes and predict information that would probably be of interest to them. Most of these approaches rely on the collaborative paradigm (often exploiting machine learning techniques) and do not take into account the huge amount of knowledge, both structured and non-structured ones, describing the domain of interest of the recommendation engine. Although very effective in predicting relevant items, collaborative approaches miss some very interesting features that go beyond the accuracy of results and move in the direction of providing novel and diverse results as well as generating an explanation for the recommended items. Furthermore, this side information becomes crucial when a conversational interaction is implemented, in particular for the preference elicitation, explanation, and critiquing steps. The 4th Knowledge-aware and Conversational Recommender Systems (KaRS) Workshop focuses on all aspects related to the exploitation of external and explicit knowledge sources to feed and build a recommendation engine, and on the adoption of interactions based on the conversational paradigm. The aim is to go beyond the traditional accuracy goal and to start a new generation of algorithms and approaches with the help of the methodological diversity embodied in fields such as Machine Learning (ML), Human-Computer Interaction (HCI), Information Retrieval (IR), and Information Systems (IS). Consequently, the focus lies on works improving the user experience and following goals such as user engagement and satisfaction or customer value. The aim of this fourth edition of KaRS is to bring together researchers and practitioners around the topics of designing and evaluating novel approaches for recommender systems in order to: * share research and techniques, including new design technologies and evaluation methodologies; * identify next key challenges in the area; * identify emerging topics in the field. [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 interests 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 - 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 - User Modeling and interfaces: - Critiquing and user's 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] Submissions of full research papers must be in English, in PDF format in the CEUR-WS two-column conference format available at: http://ceur-ws.org/Vol-XXX/CEURART.zip or at: https://www.overleaf.com/latex/templates/template-for-submissions-to-ceur-w… if an Overleaf template is preferred. Submission will be peer-reviewed and accepted papers will appear in the CEUR workshop series. 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. The conference language is English. 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). Each accepted long paper will be included in the CEUR online Workshop proceedings and presented in a plenary session as part of the Workshop program. * 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 to 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). Each accepted short paper will be included in the CEUR online Workshop proceedings * 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). Original Position/Discussion accepted papers will be included in the CEUR online Workshop proceedings. Selected Position/Discussion papers will be invited as oral presentations. The review process is single-blind. Submitted papers will be evaluated according to their originality, technical content, style, clarity, and relevance to the workshop. Moreover, following the RecSys 2022 guidelines, reviewers will be asked to comment on whether the length is appropriate for the contribution. Shorter papers should generally report on advances that can be described, set into context, and evaluated concisely. Longer papers should reflect substantial contributions of lasting value. Short and long paper submissions must be original work and may not be under submission to another venue at the time of review. Accepted papers will appear in the workshop proceedings. Submission will be through Easychair at: https://easychair.org/conferences/?conf=kars2022 [IMPORTANT DATES] * Paper submissions due: August 5th, 2022 * Paper acceptance notification: August 27th, 2022 * Camera ready deadline: September 10th, 2022 * Workshop day: Sep 18th-23rd, 2022 Deadlines refer to 23:59 (11:59pm) in the AoE (Anywhere on Earth) time zone. Eng. Vito Walter Anelli Ph.D. Information Systems Research Group Department of Electrical & Information Engineering Polytechnic University of Bari p: 00390805963641 a: Via Orabona 4 70125 Bari (BA) Italy w: sisinflab.poliba.it/anelli/ e: vitowalter.anelli(a)poliba.it 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.

2 years, 2 months

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PhD position on "Relational data analysis on a DBMS – agregation based on relational algebra" (Strasbourg, France)

by BRAUD Agnes (ILL)

Dear all, We are looking for candidates for a PhD position on "Relational data analysis on a DBMS – agregation based on relational algebra" inside the Data Science and Knowledge team of ICube Laboratory (Université de Strasbourg - CNRS - ENGEES - INSA). Position description: [ https://seafile.unistra.fr/f/c30193f9729147f2ac24/ | https://seafile.unistra.fr/f/c30193f9729147f2ac24/ ] We would be grateful if you could forward this offer to potential candidates. Best regards, Agnès Braud.

2 years, 2 months

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1st Call For Participation - CLA 2022: The 16th International Conference on Concept Lattices and Their Applications

by Ben Yahia Sadok

LA 2022: The 16th International Conference on Concept Lattices and Their Applications The 16th International Conference on Concept Lattices and Their Applications June 20–22, 2022. Conference venue: Tallinnk SPA hotel ( Tallinn, Estonia) (https://www.tallinkhotels.com/tallink-spa-conference-hotel) [ https://cs.ttu.ee/events/cla2020/ | https://cs.ttu.ee/events/cla2022/ ] Invited speakers: 1. [ https://ai.ugent.be/people/BernardDeBaets.en.html | Bernard De Baets ] (Ghent University, Belgium): Putting order into the ordering of random variables 2. John F. Sowa ( Kyndi, Inc., San Mateo, CA, USA ): Automated and semi-automated tools for interoperable systems 3. [ https://www.math.sk/mesiar/ | Radko Mesiar ] ( Slovak University of Technology , Bratislava, Slovakia ): Aggregation functions 4. [ https://www.ksi.mff.cuni.cz/~vojtas/ | Peter Vojtáš ] ( [ https://www.mff.cuni.cz/en | Faculty of Mathematics and Physics ] , [ https://cuni.cz/UKEN-1.html | Charles University): ] Galois-Tukey connections in experiments 5. [ https://sites.google.com/site/boualembenatallahwebsite/ | Boualem Benatallah ] (DCU, Ireland ): AI Service Augmentation: Challenges and Directions Tutorial M ANAGING AND LINKING DATA WITH KG USING [ http://poolparty.biz/ | PP SEMANTIC SUITE ] (https://cs.ttu.ee/events/cla2022/?page=tutorial) - Workshop ETAFCA'2022 - Existing Tools and Applications for Formal Concept Analysis ( https://cs.ttu.ee/events/etafca-2022/ ) . . Accepted papers https://cs.ttu.ee/events/cla2022/?page=papers

2 years, 2 months

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fca-list May 2022