Subject categorisation experiments with AI in MTMThdl:21.15109/ARP/VWQFD2ARP2026-05-082Micsik, András; Tanácsi, Roland, 2026, "Subject categorisation experiments with AI in MTMT", https://hdl.handle.net/21.15109/ARP/VWQFD2, ARP, V2Subject categorisation experiments with AI in MTMThdl:21.15109/ARP/VWQFD2Micsik, AndrásTanácsi, Roland2025-11-15PythonRRF-2.3.1-21-2022-00004ARPMicsik, AndrásMicsik, András2026-02-03Computer and Information ScienceSzámítástechnika és informatikasubject classificationscientific categorizationtransformer modelsSupport Vector Classifierdata cleaninglarge language modelsartificial intelligenceCode, sample data and results for subject categorisation experiments with AI in MTMT<a href="http://creativecommons.org/licenses/by-nc-nd/4.0">CC BY-NC-ND 4.0</a>Tanácsi, R., & Micsik, A. (2026). A Comparative Evaluation of AI Approaches to Large-Scale Scientific Subject Classification. Big Data and Cognitive Computing, 10(5), 151.10.3390/bdcc10050151Tanácsi, R., & Micsik, A. (2026). A Comparative Evaluation of AI Approaches to Large-Scale Scientific Subject Classification. Big Data and Cognitive Computing, 10(5), 151.README.txttext/plainlvl4-mtmt-large-multiclass-svm-rbf.zipapplication/octet-streamsvm_rbf_confusion_matrix_percent.csvtext/csvannif.csvtext/csvembedding_scikit.csvtext/csvscibert_lvl3.csvtext/csvscibert_lvl4.csvtext/csvscibert_lvl4_subtopics.csvtext/csvscibert_moe.csvtext/csvfrascati_mapping.jsonapplication/jsonsample_evaluation_data.csvtext/csvsample_evaluation_data.npyapplication/octet-streamsample_training_data.csvtext/csvsample_training_data.npyapplication/octet-streameval_svm_rbf.pytext/x-pythonrequirements.txttext/plaintrain_svm_rbf.pytext/x-python