June 2021 - sem-grd - lists.ogf.org

[CFP] IECARTE 2021
by Editor-in- Chief 31 Jul '23

31 Jul '23

*2021 Conference**CALL FOR PAPERS**(Accepted & Presented Papers will be Published by Peer Reviewed Journals and Submitted for SCI and SCOPUS)* 1st International E–Conference on Applied Research Trends in Engineering* - IECARTE 2021**14-15 December 2021**Website**:- * *http://www.ijces.com/1st-iecarte/* <http://www.ijces.com/1st-iecarte/> Greetings.,hope you are safe and doing well. The objective of this International conference is to provide opportunities for the Researchers, Academicians, Industry persons and students to interact and exchange ideas, experience and expertise in the current trend and strategies for applied research problems in engineering. Besides this, participants will also be enlightened about vast avenues, current and emerging technological developments in the field of engineering in this era and its applications, will be thoroughly explored and discussed. Authors can submit the papers in following related areas - Computer Engineering - Electrical Engineering - Electronics Engineering - Civil Engineering - Structural Engineering - Mathematical Engineering - Mechanical Engineering - Ant interdisciplinary domain in view of above *Publication* : All the papers accepted and presented in the conference is going to be published of peer reviewed journals and submitted for possible consideration in SCOPUS and SCI database. Paper Submission link <https://docs.google.com/forms/d/e/1FAIpQLSeecU4_BKi_5i2qBMlGqvuJV4rDRoQv-J4…> *Important Dates * - *Submission Deadline: 1st August 2021* - *Acceptance Notification: 2nd Oct 2021 (On or before)* - *Camera-Ready version Submission Deadline: 5th November 2021* - *Registration Deadline: 30th November 2021* - *Conference Dates:14-15 December 2021* Note: IECARTE is organised in virtual mode because of COVID prolongs. Send your inquiries through Email to *ijces.editor(a)gmail.com* <ijces.editor(a)gmail.com> *With Best Regards,* *Organising Team IECARTE 2021.*

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CfP ISWC 2021 - Call for Research, In-Use, Resource, Doctoral Consortium papers
by International Semantic Web Conference 28 Jun '21

28 Jun '21

20th International Semantic Web Conference (ISWC 2021) Virtual, October 24-28, 2021 https://iswc2021.semanticweb.org In this announcement: 1. Call for Research papers 2. Call for In-Use papers 3. Call for Resource papers 4. Call for Doctoral Consortium papers 1. Call for Research papers ******************************************* In this track of ISWC 2021, we are looking for novel and significant research contributions addressing theoretical, analytical and empirical aspects of the Semantic Web. While we welcome work that relates to the W3C Semantic Web recommendations (e.g., RDF, OWL, SPARQL, etc.), we also encourage contributions to research at the intersection of the Semantic Web and other scientific disciplines. Submissions to the research track should describe original, significant, and replicable research on the Semantic Web. All papers must include method evaluations that are rigorous, repeatable and reproducible. This will be one of the key reviewing criteria. We also strongly encourage papers that provide links to the data sets, source code and queries used to evaluate their approach, and/or live deployments. Topics of interest and further details: https://iswc2021.semanticweb.org/research-track Track Chairs: - Eva Blomqvist (University of Linköping, Sweden) - Andreas Hotho (University of Würzburg, Germany) Contact: iswc2021-program(a)easychair.org 2. Call for In-Use papers ******************************************* The In-Use track at ISWC 2021 continues the tradition of demonstrating and sharing the increasing adoption of Semantic Web technologies by providing a forum for the community to explore the benefits and challenges of applying such technologies in concrete, practical use cases, beyond the research communities from which they originate, in contexts ranging from industry to government and society. The In-Use track thus seeks submissions describing applied and validated solutions such as software tools, systems or architectures that benefit from the use of Semantic Web technologies (including, but not limited to, technologies based on the Semantic Web standards). Topics of interest and further details: https://iswc2021.semanticweb.org/in-use-call Track Chairs: - Ying Ding (University of Texas at Austin, USA) - Payam Barnaghi (Imperial College London, UK) Contact: iswc2021-in-use(a)easychair.org 3. Call for Resource papers ******************************************* The ISWC 2021 Resources Track aims to promote the sharing of resources which support, enable or utilise semantic web research. Resources include, but not restricted to: datasets, ontologies/vocabularies, ontology design patterns, evaluation benchmarks or methods, software tools/services, APIs and software frameworks, workflows, crowdsourcing task designs, protocols, methodologies and metrics, that have contributed or may contribute to the generation of novel scientific work. In particular, we encourage the sharing of such resources following best and well-established practices within the Semantic Web community. As such, this track calls for contributions that provide a concise and clear description of a resource and its usage. Topics of interest and further details: https://iswc2021.semanticweb.org/resources-track Track Chairs: - Stefan Dietze (GESIS, Cologne & Heinrich-Heine-University Düsseldorf, Germany)_ - Achille Fokoue (IBM Research, Yorktown Heights, NY, USA) ***** Important Dates (common to all paper tracks above) ***** - Abstracts Due: 12 April 2021 - Full Papers Due: 19 April 2021 - Author Rebuttals: 2–6 June 2021 - Notifications: 23 June 2021 4. Call for Doctoral Consortium papers ******************************************* The ISWC 2021 Doctoral Consortium (DC) will provide PhD students with an opportunity to: ● present and discuss their research ideas in a supportive, formative and yet critical environment; ● receive feedback from mentors, typically senior members of the Semantic Web research community, and peers; ● explore career pathways available after completing their PhD degree, and finally ● network and build collaborations with other members of the community. The event is intended for students who are midway through their PhD, therefore at a stage where they have articulated a reasonably detailed research proposal, preferably supported by some preliminary results. The aim is to support the students in refining their proposal and suggest possible ways to improve their research plan and achieve results with prospective greater impact. While doctoral degrees can vary in format and conduct, we aim this Call for Papers to PhD candidates in their second, or early in their third year and who will have already partially investigated some specific problems. Students will be required to submit a paper to the doctoral consortium, structured like a research proposal. All proposals submitted to the Doctoral Consortium will undergo a rigorous review process by the International Programme Committee, who will provide detailed and constructive feedback and select those submissions to be presented at the Doctoral Consortium. If accepted, students will have to register and attend the event, which will include a range of interactive activities. Details: https://iswc2021.semanticweb.org/doctoral-consortium-call DC Chairs: - Miriam Fernandez (Open University, UK) - Valentina Tamma (University of Liverpool, UK) ***** Important Dates (DC track) ***** - Papers due: 3 May, 2021 - Notification to proposers: 31 May 2021 - DC Day: 25 October, 2021 *** All deadlines are AoE (Anywhere on Earth) *** Submission link for all papers: https://easychair.org/conferences/?conf=iswc2021 Follow ISWC on social media: - Twitter: @iswc_conf #iswc_conf (https://twitter.com/iswc_conf) - LinkedIn: https://www.linkedin.com/groups/13612370 - Facebook: https://www.facebook.com/ISWConf The ISWC 2021 Organising Team https://iswc2021.semanticweb.org/organizing-committee

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[CFP] DEADLINE EXTENSION for 1st International Workshop on Ontology Uses and Contribution to Artificial Intelligence @ KR-2021
by Sarra Ben Abbès 28 Jun '21

28 Jun '21

Dear colleagues and researchers, Please consider submitting a paper for the 1st International workshop on "Ontology Uses and Contribution to Artificial Intelligence" which will be held online or in Hanoi, Vietnam - November 6-12, 2021. * **** OnUCAI - CALL FOR PAPERS **** * * Ontology Uses and Contribution to Artificial Intelligence* * 1st International Workshop, in conjunction with *KR 2021 <https://kr2021.kbsg.rwth-aachen.de/> * November 6-12, 2021 - Online or in Hanoi, Vietnam* https://sites.google.com/view/onucai-kr2021 ** Important dates ** - *Workshop paper submission due: *July 02, 2021 *July 19, 2021* - *Workshop paper notifications: *August 06, 2021 - *Workshop paper camera-ready versions due: *September 06, 2021 - *Workshop registration deadline: *TBA - *Workshop: *November 06-12, 2021 All deadlines are 23:59 anywhere on earth (UTC-12) ** Workshop description ** An ontology is well known to be the best way to represent knowledge in a domain of interest. It is defined by Gruber as “an explicit specification of a conceptualization”. It allows us to represent explicitly and formally existing entities, their relationships and their constraints in an application domain. This representation is the most suitable and beneficial way to solve many challenging problems related to the information domain (e.g., knowledge representation, knowledge sharing, knowledge reusing, automated reasoning, knowledge capitalizing and ensuring semantic interoperability among heterogeneous systems). Using ontology has many advantages, among them we can cite ontology reusing, reasoning and explanation, commitment and agreement on a domain of discourse, ontology evolution and mapping, etc. As a field of artificial intelligence (AI), ontology aims at representing knowledge based on declarative and symbolic formalization. Combining this symbolic field with computational fields of IA such as Machine Learning (ML), Deep Learning (DL), Probabilistic Graphical Models (PGMs), Computer Vision (CV) and Natural Languages Processing (NLP) is a promising association. Indeed, ontological modeling plays a vital role to help AI reducing the complexity of the studied domain and organizing information inside it. It broadens AI’s scope allowing it to include any data type as it supports unstructured, semi-structured, or structured data format which enables smoother data integration. The ontology also assists AI for interpretation process, learning, enrichment, prediction, semantic disambiguation and discovering of complex inferences. Finally, the ultimate goal of ontologies is the ability to be integrated in a software to make sense of all information. In the last decade, ontologies are increasingly being used to provide background knowledge for several AI domains in different sectors (e.g. energy, transport, health, banking and insurance, etc.). Some of these AI domains are: - Machine learning and deep learning: semantic data selection, semantic data pre-processing, semantic data transformation, semantic data prediction, semantic clustering correction of the outputs, semantic enrichment with ontological concepts, use the semantic structure for promoting distance measure, etc. - Probabilistic Graphical Models: learning PGM (structure or parameters) using ontologies, probabilistic semantic reasoning, semantic causality and probability, etc. - Computer Vision: semantic image processing, semantic image classification, semantic object recognition/classification, etc. - Blockchain: semantic transactions, interoperable blockchain systems, etc. - Natural Language Processing: semantic text mining, semantic text classification, semantic role labelling, semantic machine translation, semantic question answering, ontology based text summarizing, semantic recommendation systems, etc. - Robotics: semantic task composition, task assignment, communication, cooperation and coordination, etc. - Voice-video-speech: semantic voice recognition, semantic speech annotation, etc. - Game Theory: semantic definition of specific games, semantic rules and goals definition, etc. - etc. ** Objective ** This workshop aims at highlighting recent and future advances on the role of ontologies and knowledge graphs in different domains of AI and how it can be used in order to reduce the semantic gap between the data, applications, machine learning process, etc., in order to obtain a semantic-aware approaches. In addition, the goal of this workshop is to bring together an area for experts from industry, science and academia to exchange ideas and discuss results of on-going research in ontologies and AI approaches. We invite the submission of original works that is related -- but are not limited to -- the topics below. ** Topics of interests ** - Ontology for Machine Learning/Deep Learning - Ontology for Probabilistic Graphical Models - Ontology for Federated Machine Learning - Ontology for Smart Contracts - Ontology for Computer Vision - Ontology for Natural Language Processing - Ontology for Robotics and Multi-agent Systems - Ontology for Voice-video-speech - Ontology for Game Theory - and so on. ** Submission * * The workshop is open to submit unpublished work resulting from research that presents original scientific results, methodological aspects, concepts and approaches. All submissions are not anonymous and must be PDF documents written in English and formatted using the following style files: *KR2021_authors_kit <https://www.google.com/url?q=https%3A%2F%2Fkr2021.kbsg.rwth-aachen.de%2Fdow…>* Papers are to be submitted through the workshop's *EasyChair <https://www.google.com/url?q=https%3A%2F%2Feasychair.org%2F&sa=D&sntz=1&usg…>* submission page. We welcome the following types of contributions: - *Full papers* of up to 9 pages, including abstract, figures and appendices (if any), but excluding references and acknowledgements: Finished or consolidated R&D works, to be included in one of the Workshop topics. - *Short papers* of up to 4 pages, excluding references and acknowledgements: Ongoing works with relevant preliminary results, opened to discussion. At least one author of each accepted paper must register for the workshop, in order to present the paper. For further instructions, please refer to the *KR 2021 <https://www.google.com/url?q=https%3A%2F%2Fkr2021.kbsg.rwth-aachen.de%2F&sa…>* page. ** Workshop chairs ** - Sarra Ben Abbès, Engie, France - Lynda Temal, Engie, France - Nada Mimouni, CNAM, France - Ahmed Mabrouk, Engie, France - Philippe Calvez, Engie, France ** Program Committee ** - Shridhar Devamane, Physical Design Engineer, Tecsec Technologies, Bangalore, India - Philippe Leray, Professor at University of Nantes - Stefan FENZ, key researcher at SBA Research and Senior Scientist at Vienna University of Technology <https://informatics.tuwien.ac.at/people/stefan-fenz> - Olivier Dameron, Professor at Université de Rennes I, Dyliss team, Irisa / Inria Rennes-Bretagne Atlantique - Aarón Ayllón Benitez, Phd in bioinformatique, ontology leader at BASF digital solutions - François Scharffe, Researcher on Knowledge based AI, New York, United States - Maxime Lefrançois, Associate Professor at Saint Etienne University, France - Pierre Maret, The QA Company & Saint Etienne University, France **Publication* The best papers from this workshop may be included in the supplementary proceedings of KR 2021.

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[CFP] 1st International Workshop on Ontology Uses and Contribution to Artificial Intelligence
by Sarra Ben Abbès 22 Jun '21

22 Jun '21

Dear colleagues and researchers, Please consider submitting a paper for the 1st International workshop on "Ontology Uses and Contribution to Artificial Intelligence" which will be held online or in Hanoi, Vietnam - November 6-12, 2021. * **** OnUCAI - CALL FOR PAPERS **** * * Ontology Uses and Contribution to Artificial Intelligence* * 1st International Workshop, in conjunction with *KR 2021 <https://kr2021.kbsg.rwth-aachen.de/> * November 6-12, 2021 - Online or in Hanoi, Vietnam* https://sites.google.com/view/onucai-kr2021 ** Important dates ** - *Workshop paper submission due: *July 02, 2021 - *Workshop paper notifications: *August 06, 2021 - *Workshop paper camera-ready versions due: *September 06, 2021 - *Workshop registration deadline: *TBA - *Workshop: *November 06-12, 2021 All deadlines are 23:59 anywhere on earth (UTC-12) ** Workshop description ** An ontology is well known to be the best way to represent knowledge in a domain of interest. It is defined by Gruber as “an explicit specification of a conceptualization”. It allows us to represent explicitly and formally existing entities, their relationships and their constraints in an application domain. This representation is the most suitable and beneficial way to solve many challenging problems related to the information domain (e.g., knowledge representation, knowledge sharing, knowledge reusing, automated reasoning, knowledge capitalizing and ensuring semantic interoperability among heterogeneous systems). Using ontology has many advantages, among them we can cite ontology reusing, reasoning and explanation, commitment and agreement on a domain of discourse, ontology evolution and mapping, etc. As a field of artificial intelligence (AI), ontology aims at representing knowledge based on declarative and symbolic formalization. Combining this symbolic field with computational fields of IA such as Machine Learning (ML), Deep Learning (DL), Probabilistic Graphical Models (PGMs), Computer Vision (CV) and Natural Languages Processing (NLP) is a promising association. Indeed, ontological modeling plays a vital role to help AI reducing the complexity of the studied domain and organizing information inside it. It broadens AI’s scope allowing it to include any data type as it supports unstructured, semi-structured, or structured data format which enables smoother data integration. The ontology also assists AI for interpretation process, learning, enrichment, prediction, semantic disambiguation and discovering of complex inferences. Finally, the ultimate goal of ontologies is the ability to be integrated in a software to make sense of all information. In the last decade, ontologies are increasingly being used to provide background knowledge for several AI domains in different sectors (e.g. energy, transport, health, banking and insurance, etc.). Some of these AI domains are: - Machine learning and deep learning: semantic data selection, semantic data pre-processing, semantic data transformation, semantic data prediction, semantic clustering correction of the outputs, semantic enrichment with ontological concepts, use the semantic structure for promoting distance measure, etc. - Probabilistic Graphical Models: learning PGM (structure or parameters) using ontologies, probabilistic semantic reasoning, semantic causality and probability, etc. - Computer Vision: semantic image processing, semantic image classification, semantic object recognition/classification, etc. - Blockchain: semantic transactions, interoperable blockchain systems, etc. - Natural Language Processing: semantic text mining, semantic text classification, semantic role labelling, semantic machine translation, semantic question answering, ontology based text summarizing, semantic recommendation systems, etc. - Robotics: semantic task composition, task assignment, communication, cooperation and coordination, etc. - Voice-video-speech: semantic voice recognition, semantic speech annotation, etc. - Game Theory: semantic definition of specific games, semantic rules and goals definition, etc. - etc. ** Objective ** This workshop aims at highlighting recent and future advances on the role of ontologies and knowledge graphs in different domains of AI and how it can be used in order to reduce the semantic gap between the data, applications, machine learning process, etc., in order to obtain a semantic-aware approaches. In addition, the goal of this workshop is to bring together an area for experts from industry, science and academia to exchange ideas and discuss results of on-going research in ontologies and AI approaches. We invite the submission of original works that is related -- but are not limited to -- the topics below. ** Topics of interests ** - Ontology for Machine Learning/Deep Learning - Ontology for Probabilistic Graphical Models - Ontology for Federated Machine Learning - Ontology for Smart Contracts - Ontology for Computer Vision - Ontology for Natural Language Processing - Ontology for Robotics and Multi-agent Systems - Ontology for Voice-video-speech - Ontology for Game Theory - and so on. ** Submission * * The workshop is open to submit unpublished work resulting from research that presents original scientific results, methodological aspects, concepts and approaches. All submissions are not anonymous and must be PDF documents written in English and formatted using the following style files: *KR2021_authors_kit <https://www.google.com/url?q=https%3A%2F%2Fkr2021.kbsg.rwth-aachen.de%2Fdow…>* Papers are to be submitted through the workshop's *EasyChair <https://www.google.com/url?q=https%3A%2F%2Feasychair.org%2F&sa=D&sntz=1&usg…>* submission page. We welcome the following types of contributions: - *Full papers* of up to 9 pages, including abstract, figures and appendices (if any), but excluding references and acknowledgements: Finished or consolidated R&D works, to be included in one of the Workshop topics. - *Short papers* of up to 4 pages, excluding references and acknowledgements: Ongoing works with relevant preliminary results, opened to discussion. At least one author of each accepted paper must register for the workshop, in order to present the paper. For further instructions, please refer to the *KR 2021 <https://www.google.com/url?q=https%3A%2F%2Fkr2021.kbsg.rwth-aachen.de%2F&sa…>* page. ** Workshop chairs ** - Sarra Ben Abbès, Engie, France - Lynda Temal, Engie, France - Nada Mimouni, CNAM, France - Ahmed Mabrouk, Engie, France - Philippe Calvez, Engie, France ** Program Committee ** - Shridhar Devamane, Physical Design Engineer, Tecsec Technologies, Bangalore, India - Philippe Leray, Professor at University of Nantes - Stefan FENZ, key researcher at SBA Research and Senior Scientist at Vienna University of Technology <https://informatics.tuwien.ac.at/people/stefan-fenz> - Olivier Dameron, Professor at Université de Rennes I, Dyliss team, Irisa / Inria Rennes-Bretagne Atlantique - Aarón Ayllón Benitez, Phd in bioinformatique, ontology leader at BASF digital solutions - François Scharffe, Researcher on Knowledge based AI, New York, United States - Maxime Lefrançois, Associate Professor at Saint Etienne University, France - Pierre Maret, The QA Company & Saint Etienne University, France **Publication* The best papers from this workshop may be included in the supplementary proceedings of KR 2021.

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[CFP] 1st International Workshop on Ontology Uses and Contribution to Artificial Intelligence
by Sarra Ben Abbès 08 Jun '21

08 Jun '21

Dear colleagues and researchers, Please consider submitting a paper for the 1st International workshop on "Ontology Uses and Contribution to Artificial Intelligence" which will be held online or in Hanoi, Vietnam - November 6-12, 2021. * **** OnUCAI - CALL FOR PAPERS **** * * Ontology Uses and Contribution to Artificial Intelligence* * 1st International Workshop, in conjunction with *KR 2021 <https://kr2021.kbsg.rwth-aachen.de/> * November 6-12, 2021 - Online or in Hanoi, Vietnam* https://sites.google.com/view/onucai-kr2021 ** Important dates ** - *Workshop paper submission due: *July 02, 2021 - *Workshop paper notifications: *August 06, 2021 - *Workshop paper camera-ready versions due: *September 06, 2021 - *Workshop registration deadline: *TBA - *Workshop: *November 06-12, 2021 All deadlines are 23:59 anywhere on earth (UTC-12) ** Workshop description ** An ontology is well known to be the best way to represent knowledge in a domain of interest. It is defined by Gruber as “an explicit specification of a conceptualization”. It allows us to represent explicitly and formally existing entities, their relationships and their constraints in an application domain. This representation is the most suitable and beneficial way to solve many challenging problems related to the information domain (e.g., knowledge representation, knowledge sharing, knowledge reusing, automated reasoning, knowledge capitalizing and ensuring semantic interoperability among heterogeneous systems). Using ontology has many advantages, among them we can cite ontology reusing, reasoning and explanation, commitment and agreement on a domain of discourse, ontology evolution and mapping, etc. As a field of artificial intelligence (AI), ontology aims at representing knowledge based on declarative and symbolic formalization. Combining this symbolic field with computational fields of IA such as Machine Learning (ML), Deep Learning (DL), Probabilistic Graphical Models (PGMs), Computer Vision (CV) and Natural Languages Processing (NLP) is a promising association. Indeed, ontological modeling plays a vital role to help AI reducing the complexity of the studied domain and organizing information inside it. It broadens AI’s scope allowing it to include any data type as it supports unstructured, semi-structured, or structured data format which enables smoother data integration. The ontology also assists AI for interpretation process, learning, enrichment, prediction, semantic disambiguation and discovering of complex inferences. Finally, the ultimate goal of ontologies is the ability to be integrated in a software to make sense of all information. In the last decade, ontologies are increasingly being used to provide background knowledge for several AI domains in different sectors (e.g. energy, transport, health, banking and insurance, etc.). Some of these AI domains are: - Machine learning and deep learning: semantic data selection, semantic data pre-processing, semantic data transformation, semantic data prediction, semantic clustering correction of the outputs, semantic enrichment with ontological concepts, use the semantic structure for promoting distance measure, etc. - Probabilistic Graphical Models: learning PGM (structure or parameters) using ontologies, probabilistic semantic reasoning, semantic causality and probability, etc. - Computer Vision: semantic image processing, semantic image classification, semantic object recognition/classification, etc. - Blockchain: semantic transactions, interoperable blockchain systems, etc. - Natural Language Processing: semantic text mining, semantic text classification, semantic role labelling, semantic machine translation, semantic question answering, ontology based text summarizing, semantic recommendation systems, etc. - Robotics: semantic task composition, task assignment, communication, cooperation and coordination, etc. - Voice-video-speech: semantic voice recognition, semantic speech annotation, etc. - Game Theory: semantic definition of specific games, semantic rules and goals definition, etc. - etc. ** Objective ** This workshop aims at highlighting recent and future advances on the role of ontologies and knowledge graphs in different domains of AI and how it can be used in order to reduce the semantic gap between the data, applications, machine learning process, etc., in order to obtain a semantic-aware approaches. In addition, the goal of this workshop is to bring together an area for experts from industry, science and academia to exchange ideas and discuss results of on-going research in ontologies and AI approaches. We invite the submission of original works that is related -- but are not limited to -- the topics below. ** Topics of interests ** - Ontology for Machine Learning/Deep Learning - Ontology for Probabilistic Graphical Models - Ontology for Federated Machine Learning - Ontology for Smart Contracts - Ontology for Computer Vision - Ontology for Natural Language Processing - Ontology for Robotics and Multi-agent Systems - Ontology for Voice-video-speech - Ontology for Game Theory - and so on. ** Submission * * The workshop is open to submit unpublished work resulting from research that presents original scientific results, methodological aspects, concepts and approaches. All submissions are not anonymous and must be PDF documents written in English and formatted using the following style files: *KR2021_authors_kit <https://www.google.com/url?q=https%3A%2F%2Fkr2021.kbsg.rwth-aachen.de%2Fdow…>* Papers are to be submitted through the workshop's *EasyChair <https://www.google.com/url?q=https%3A%2F%2Feasychair.org%2F&sa=D&sntz=1&usg…>* submission page. We welcome the following types of contributions: - *Full papers* of up to 9 pages, including abstract, figures and appendices (if any), but excluding references and acknowledgements: Finished or consolidated R&D works, to be included in one of the Workshop topics. - *Short papers* of up to 4 pages, excluding references and acknowledgements: Ongoing works with relevant preliminary results, opened to discussion. At least one author of each accepted paper must register for the workshop, in order to present the paper. For further instructions, please refer to the *KR 2021 <https://www.google.com/url?q=https%3A%2F%2Fkr2021.kbsg.rwth-aachen.de%2F&sa…>* page. ** Workshop chairs ** - Sarra Ben Abbès, Engie, France - Lynda Temal, Engie, France - Nada Mimouni, CNAM, France - Ahmed Mabrouk, Engie, France - Philippe Calvez, Engie, France ** Program Committee ** - Shridhar Devamane, Physical Design Engineer, Tecsec Technologies, Bangalore, India - Philippe Leray, Professor at University of Nantes - Stefan FENZ, key researcher at SBA Research and Senior Scientist at Vienna University of Technology <https://informatics.tuwien.ac.at/people/stefan-fenz> - Olivier Dameron, Professor at Université de Rennes I, Dyliss team, Irisa / Inria Rennes-Bretagne Atlantique - Aarón Ayllón Benitez, Phd in bioinformatique, ontology leader at BASF digital solutions **Publication* The best papers from this workshop may be included in the supplementary proceedings of KR 2021.

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Second Call for Papers: KGSWC-2021 with the Opportunity of SCI/ESCI-Scopus Journal for Extended Version
by Dr. Sanju Tiwari 04 Jun '21

04 Jun '21

##apologies if multiple copies received## *######Second Call for Papers######* *KGSWC-2021Third Ibero-American Knowledge Graph and Semantic Web Conference joint with Second Indo-American Knowledge Graph and Semantic Web Conference*22-24 November 2021 Texas A & M University, Kingsville http://www.kgswc.org Dear Researcher We are glad to confirm KGSWC-2021 will be published by Springer CCIS Proceedings. We invite to enjoy the following events and talks: a) Keynotes *(Top Experts of Knowledge Graph & Semantic Web Community*) b) Hackathon supported by Prof Amit Sheth and Team c) Winter School (Worldwide Academician on Knowledge Graphs & Semantic Web) d) Workshops (Based on Different Continents) We also have an exciting opportunity to invite accepted papers in the following *SCIE/ESCI* journals. *a) **Data Technologies and Applications (SCIE)* https://www.emeraldgrouppublishing.com/journal/dta *b) **Journal of King Saud University – Computer and Information Sciences (SCIE)* https://www.journals.elsevier.com/journal-of-king-saud-university-computer-… sciences *c) **International Journal of Web Information Systems (ESCI, SCOPUS)* https://www.emeraldgrouppublishing.com/journal/ijwis *d) **International Journal of Information System Modeling and Design (IJISMD) (ESCI, Scopus)* https://www.igi-global.com/journal/international-journal-information-system… *Submission Link*: https://easychair.org/conferences/?conf=kgswc2021 *Important Dates* ============== Submission Deadline July 31, 2021 Notification Due September 30, 2021 Final Version Due October 31, 2021 Some of you are the evidence of our previous events that are successfully held in Cuba, 2019 and Mexico, 2020. The registration fees of all KGSWC-2020 events were fully free due to COVID-19 impact. Proceedings of previous events are available : *Proceeding 2019:* https://www.springer.com/gp/book/9783030213947 *Proceeding 2020:* https://www.springer.com/gp/book/9783030653835 *Please feel free to contact the organizers for any queries.* -- Regards Dr. Sanju Tiwari (PhD, Post-Doc), SMIEEE Sr. Researcher, Universidad Autonoma de Tamaulipas, Mexico Adjunct Professor, Vardhaman College of Engineering, Hyderabad, India Ph.D. Supervisor, Rai University, Ahmedabad, Gujarat, India DAAD Post-Doc-Net AI Fellow General Chair *KGSWC-2021* (Second Indo-American Conference) http://www.kgswc.org/indo-american/ Senior Member IEEE Member Machine Intelligence Research Labs(MIR Lab), USA

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