This research cluster focuses on the development of advanced Natural Language Processing (NLP) technologies to enable intelligent interaction between humans and machines through natural language. The cluster explores methods for language understanding, text analytics, information extraction, sentiment analysis, machine translation, conversational AI, large language models, and multilingual language technologies. By leveraging artificial intelligence, machine learning, and data engineering techniques, the cluster aims to transform unstructured textual data into actionable knowledge and support data-driven decision-making across industries, public services, healthcare, education, and digital ecosystems.
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Hybrid Deep Learning CNN-Bidirectional LSTM and Manhattan Distance for Japanese Automated Short Answer Grading: Use case in Japanese Language Studies
Author: Ratna A.A.P., Purnamasari P.D., Anandra N.K., Luhurkinanti D.L.
Published in: ACM International Conference Proceeding Series
Date of Publication: 2022
DOI: 10.1145/3571662.3571666