Cfp June 2021

cfp@alice.wu.ac.at

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Fwd: [AISWorld] CfP HICSS-55: mini track on Explainable Artificial Intelligence (XAI) with publication opportunity in Electronic Markets
by Gustaf Neumann 01 Jun '21

01 Jun '21

-------- Forwarded Message -------- Subject: [AISWorld] CfP HICSS-55: mini track on Explainable Artificial Intelligence (XAI) with publication opportunity in Electronic Markets Date: Tue, 1 Jun 2021 08:52:04 +1000 From: Babak Abedin <babak.abedin(a)gmail.com> To: aisworld(a)lists.aisnet.org Dear colleagues, We are happy to introduce the minitrack on “*Explainable Artificial Intelligence (XAI)*” at *HICSS 55* (submission deadline: *June 15th*, 2021). We provide the opportunity for (extended) best papers of this minitrack to be *fast-tracked* to the journal* Electronic Markets *(Special Issue on “*Explainable and Responsible Artificial Intelligence*”*, *CfP will follow). If you have any questions, please do not hesitate to contact Christian Meske (christian.meske(a)fu-berlin.de) Yours sincerely, Christian Meske, Babak Abedin, Mathias Klier, Fethi Rabhi ********************************************************************* *Call for Papers: “Explainable Artificial Intelligence (XAI)” Minitrack at the 55th Hawaii International Conference on System Sciences (HICSS)* ********************************************************************* The use of Artificial Intelligence (AI) in the context of decision analytics and service science has received significant attention in academia and practice alike. Yet, much of the current efforts have focused on advancing underlying algorithms and not on decreasing the complexity of AI systems. AI systems are still “black boxes” that are difficult to comprehend—not only for developers, but particularly for users and decision-makers. In addition, the development and use of AI is associated with many risks and pitfalls like biases in data or predictions based on spurious correlations (“Clever Hans” phenomena), which eventually may lead to malfunctioning or biased AI and hence technologically driven discrimination. This is where research on Explainable Artificial Intelligence (XAI) comes in. Also referred to as “transparent,” “interpretable,” or “understandable AI”, XAI aims to “produce explainable models, while maintaining a high level of learning performance (prediction accuracy); and enable human users to understand, appropriately, trust, and effectively manage the emerging generation of artificially intelligent partners”. With a focus on decision support, this minitrack aims to explore and extend research on how to establish explainability of intelligent black box systems—machine learning-based or not. We especially look for contributions that investigate XAI from either a developer’s or user’s perspective. We invite submissions from all application domains, such as healthcare, finance, e-commerce, retail, public administration or others. Technically and method-oriented studies, case studies as well as design science or behavioral science approaches are welcome. Topics of interest include, but are not limited to: - The developers’ perspective on XAI - - XAI to open, control and evaluate black box algorithms - Using XAI to identify bias in data - Explainability and Human-in-the-Loop development of AI - XAI to support interactive machine learning - Prevention and detection of deceptive AI explanations - XAI to discover deep knowledge and learn from AI - Designing and deploying XAI systems - Addressing user-centric requirements for XAI systems - The users’ perspective on XAI - - Theorizing XAI-human interactions - Presentation and personalization of AI explanations for different target groups - XAI to increase situational awareness, compliance behavior and task performance - XAI for transparency and unbiased decision making - Impact of explainability on AI-based decision support systems use and adoption - Explainability of AI in crisis situations - Potential harm of explainability in AI - Identifying user-centric requirements for XAI systems - The governments’ perspective on XAI - - Explainability and transparency policy guidelines - Evidence-based benefits and challenges of XAI implementations in the public sector - XAI and compliance *Submission Deadline: * June 15th, 2021 (Notification: until August 17th, 2021) Further information for authors: https://hicss.hawaii.edu/authors/ Link to minitrack descriptions: https://hicss.hawaii.edu/tracks-54/decision-analytics-and-service-science/#… *Fast track:* We provide the opportunity for (extended) best papers of this minitrack to be fast-tracked to the journal Electronic Markets (Special Issue on “Explainable and Responsible Artificial Intelligence”, CfP will follow). *Minitrack Co-Chairs: * Christian Meske Freie Universität Berlin Babak Abedin Macquarie University Mathias Klier University of Ulm Fethi Rabhi University of New South Wales _______________________________________________ AISWorld mailing list AISWorld(a)lists.aisnet.org

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Fwd: [AISWorld] [KaRS 2021] Second CfP: 3rd Knowledge-aware and Conversational Recommender Systems Workshop 2021 @ ACM RecSys
by Gustaf Neumann 01 Jun '21

01 Jun '21

-------- Forwarded Message -------- Subject: [AISWorld] [KaRS 2021] Second CfP: 3rd Knowledge-aware and Conversational Recommender Systems Workshop 2021 @ ACM RecSys Date: Tue, 1 Jun 2021 15:37:56 +0000 From: Vito Walter Anelli <vitowalter.anelli(a)poliba.it> To: aisworld(a)lists.aisnet.org <aisworld(a)lists.aisnet.org> Call for Papers Third Workshop on Knowledge-aware and Conversational Recommender Systems (KaRS 2021) https://kars-workshop.github.io/2021/ http://sisinflab.poliba.it/kars/2021/ Sep. 27th - Oct. 1st, 2021, Amsterdam, the Netherlands Submission deadline: July 29th, 2021, 2021 AoE [SCOPE] We are pleased to invite you to contribute to the Third Workshop on Knowledge-aware and Conversational Recommender Systems held in conjunction with the ACM International Conference on Recommender Systems (RecSys 2021) Amsterdam, the Netherlands, from September the 27th to October the 1st, 2021. 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 3rd 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 third 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 2021 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=kars2021 [IMPORTANT DATES] * Paper submissions due: July 29th, 2021 * Paper acceptance notification: August 21st, 2021 * Camera-ready deadline: August 28th, 2021 * Workshop day: Sep 27th - Oct 1st, 2021 Deadlines refer to 23:59 (11:59pm) 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. _______________________________________________ AISWorld mailing list AISWorld(a)lists.aisnet.org

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Fwd: [AISWorld] CFP: International Conference on Secure Knowledge Management
by Gustaf Neumann 01 Jun '21

01 Jun '21

-------- Forwarded Message -------- Subject: [AISWorld] CFP: International Conference on Secure Knowledge Management Date: Tue, 1 Jun 2021 12:50:40 +0000 From: Shah, Ankit <ankitshah(a)usf.edu> To: aisworld(a)lists.aisnet.org <aisworld(a)lists.aisnet.org> Dear Colleagues, Please consider submitting your papers at this conference. You will find the details below. Thank you. Sincerely, Ankit International Conference on Secure Knowledge Management: Call for Papers With the advent of revolutionary technologies such as artificial intelligence, machine learning, cloud computing, big data, and IoT; Secure Knowledge Management (SKM) continues to be an important research area that deals with methodologies for systematically gathering, organizing, and disseminating information in a secure manner. The recent development of Artificial Intelligence (AI) in the security arena shows a promising future, and there is no doubt that AI can provide new ideas and tools for SKM. Therefore, this conference on SKM will bring together researchers & practitioners from academia, industry, and government on a global scale. The scope and focus of SKM-2021 conference are to present and discuss the most recent innovations, trends, and concerns including practical challenges encountered and solution adopted with special emphasis on AI. SKM 2019 was held in BITS Pilani, Goa Campus, Goa, India and past iterations of SKM were held at SUNY at Buffalo, SUNY Albany, NYU, SUNY Stony Brook, UT Dallas, Rutgers University, BITS Dubai, and University of South Florida. Following the biennial tradition of the Secure Knowledge Management Workshop that began in 2004, SKM-2021 (https://www.secure-km.org/) will be held during October 8 – 9, 2021, at the Courtyard by Marriott on the Riverwalk in San Antonio. Papers offering novel research contributions in all aspects of SKM are solicited for submission. Topics of interest include, but are not limited to: * SKM in specific technology domains such as: * Artificial Intelligence * Data mining and Machine Learning * Hybrid Cloud Computing * Big Data in Collaborative Environment * Internet of Things * Cyber-Physical Systems * Healthcare * Online Social Networks * Role of SKM in Design of Secure Systems * Role of SKM in General Data Protection Regulation * SKM for Digital Payments * Risk & Security Metrics for Knowledge Management * SKM for Insider Threat Detection and Mitigation * Knowledge Management for Fake News Detection * Trust concerning Knowledge Management Submission Guidelines Only original papers should be submitted. Submissions should not substantially overlap work which has been published elsewhere or simultaneously submitted to a journal or another conference with proceedings. Papers that contain any form of plagiarism will be rejected without a review. Paper Format (All papers will be published in Springer CCIS<https://www.springer.com/series/7899> (as full papers and short papers)). * All submissions must be in English and should adhere to the LNCS/CCIS format guidelines: * Guidelines for proceedings authors (pdf)<ftp://ftp.springernature.com/cs-proceeding/svproc/guidelines/Springer_Guide…> * LaTeX2e Proceedings Templates (zip)<ftp://ftp.springernature.com/cs-proceeding/llncs/llncs2e.zip> * CCIS Consent form for the publication<https://www.secure-km.org/SKM-2019/files/Consent_Form.pdf> * Including references and appendices, full paper should be 10-20 pages in the LNCS<https://www.springer.com/gp/computer-science/lncs> / CCIS<https://www.springer.com/series/7899> one-column page format. * To facilitate the double-blind paper evaluation, authors are kindly requested to submit the paper WITHOUT any self-reference to any of the authors anywhere in the paper, including the acknowledgments section of the paper and any other reference that may disclose the authors’ identity. * Papers should be uploaded to EasyChair<https://easychair.org/conferences/?conf=skm2019> in PDF format only. After the paper submission has been successfully completed, authors will receive an automatic confirmation e-mail. Each paper should clearly indicate the nature of its technical/scientific contribution and the problems, domains or environments to which it is applicable. Peer-reviewed and selected papers will be included as proceedings with Springer in their prestigious Communications in Computer and Information Science<https://www.springer.com/series/7899> series (Scopus and DBLP indexed). Some selected papers presented at the conference will be invited for extension and further review for a fast-tracked special issue of Information Systems Frontiers<https://link.springer.com/journal/10796> (SCIE, Scopus and DBLP indexed) a Springer journal. Authors of registered papers (including posters) must guarantee that their papers will be presented at the conference. At least one FULL registration is mandatory for each accepted paper. Papers which are not presented will be excluded from the conference proceedings. Camera Ready Paper Submission Guidelines Please send the following files to EasyChair (https://easychair.org/conferences/?conf=skm2021) before July 26, 2021. * A single pdf file of the final paper. * A zip file containing all the source files (LNCS/CCIS latex format) of the final paper. * Authors response to reviewer's comments. * Duly signed “Consent to Publish Form”. * Email subject: Final Camera Ready Paper (PaperID). * Registration fee transaction receipt/screenshot. Key Dates * Paper Submission Deadline: June 21, 2021 * Acceptance Notification: July 12, 2021 * Camera Ready Deadline: July 26, 2021 * Early Bird Registration: Before August 10, 2021 * Standard Registration: After August 10, 2021 * Conference Dates: October 8 – 9, 2021 === Ankit Shah, Ph.D. Assistant Professor, Industrial and Management Systems Engineering Courtesy Assistant Professor, Computer Science and Engineering University of South Florida 4202 E. Fowler Ave. Mail-Stop: ENG-030 Tampa, FL 33620-5530 Phone: 813-974-5584 Email: ankitshah(a)usf.edu<mailto:ankitshah@usf.edu> === _______________________________________________ AISWorld mailing list AISWorld(a)lists.aisnet.org

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Cfp June 2021