Call for Papers: Submission deadline extended to Oct. 15, 2021. The Workshop on Knowledge Graphs and Big Data http://www.cci.drexel.edu/kgbigdata/ (KGBigdata 2021) Virtual, Dec 15-18, 2021 (in conjunction with IEEE Big Data 2021, https://bigdataieee.org/BigData2021/) TOPICS ------ The following is a list of topics (but not limited) related this workshop: * Big knowledge graph representation and modeling * Constructing knowledge graphs from structured and unstructured data * Big knowledge graph embeddings * Link prediction * Knowledge graph completion * Natural language processing and knowledge graph * Semantic Web, ontology and knowledge graph * Knowledge graph for recommender systems * Scalable knowledge graph reasoning and inference * Knowledge graph for big data processing * Knowledge graph applications in business, biomedical, healthcare, etc. * Knowledge graph visualization and human interaction * Knowledge graph for explainable AI * Knowledge graph alignment * Graph neural networks and big knowledge graphs * Scalable knowledge graph storage and query processing * Record linkage using knowledge graphs IMPORTANT DATES ----------------------------------- * Oct 15, 2021: Due date for full and short workshop papers submission * Nov 5, 2021: Notification of paper acceptance to authors * Nov 20, 2021: Camera-ready of accepted papers * Dec 15-18, 2021: Workshops SUBMISSION GUIDELINES ---------------------- Please submit papers through the online system: https://wi-lab.com/cyberchair/2021/bigdata21/scripts/ws_submit.php * This workshop accepts both long papers (up to 10 pages) and short/position papers (2-4 pages). * Papers should be formatted to IEEE Computer Society Proceedings Manuscript. * Formatting Guidelines ( https://www.ieee.org/conferences/publishing/templates.html ). * Papers should be in the IEEE 2-column format. * Full registration of IEEE BigData 2021 is required for at least one of the authors for participating in the workshop. ORGANIZERS --------------------------- * Yuan An, Drexel University, ya45@drexel.edu * Dejing Dou, University of Oregon, dou@cs.uoregon.edu * Yuan Ling, Amazon.com, ericalingyuan@gmail.com * Alex Kalinowski, Drexel University, ajk437@drexel.edu