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Using a Common Sense Knowledge Base to Auto Generate Multi-Dimensional Vocabulary Assessments.

, , , , , and . EDM, International Educational Data Mining Society (IEDMS), (2018)

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Content Customization for Micro Learning using Human Augmented AI Techniques., , , , , , , and . BEA@ACL, page 326-335. Association for Computational Linguistics, (2019)A Data-centric AI Framework for Automating Exploratory Data Analysis and Data Quality Tasks., , , , , and . ACM J. Data Inf. Qual., 15 (4): 44:1-44:26 (December 2023)Is Your Data Relevant?: Dynamic Selection of Relevant Data for Federated Learning., , and . AAAI, page 7859-7867. AAAI Press, (2022)Data Quality for Machine Learning Tasks., , , , , , , , , and 1 other author(s). KDD, page 4040-4041. ACM, (2021)Advances in Exploratory Data Analysis, Visualisation and Quality for Data Centric AI Systems., , , , , and . KDD, page 4814-4815. ACM, (2022)Using a Common Sense Knowledge Base to Auto Generate Multi-Dimensional Vocabulary Assessments., , , , , and . EDM, International Educational Data Mining Society (IEDMS), (2018)Automatic Generation of Leveled Visual Assessments for Young Learners., , , , , , and . AAAI, page 9713-9720. AAAI Press, (2019)Tell Me More: Digital Eyes to the Physical World for Early Childhood Learning., , , , , and . EDM, International Educational Data Mining Society (IEDMS), (2017)Data Quality Toolkit: Automatic assessment of data quality and remediation for machine learning datasets., , , , , , , , , and 3 other author(s). CoRR, (2021)Automatic Assessment of Quality of your Data for AI., , , , , , , , , and . COMAD/CODS, page 354-357. ACM, (2022)