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eBook
Knowledge Engineering and Data Mining

Contributors: Konys, Agnieszka, Nowak-Brzezińska, Agnieszka

Subject Terms: computing-intensive data, dynamic programming, loop nest tiling, parallel code, OpenMP C/C++, credit scoring, cash loans, machine learning, decision model, classification, feature selection, resampling, discretization, knowledge representation, formal ontologies, graph databases, evaluation feature selection, evaluation model, psychosocial education, recommendation systems, rank aggregation, differential evolution, supervised learning, matrix factorization, metaheuristic, clinical named entity recognition, Chinese medical text, pre-trained model, systematic review, multicriteria, MCDA, MCDM, MADM, MODM, AHP, TOPSIS, VIKOR, PROMETHEE, ANP, computer-aided design (CAD), educational data mining, engineering education, online and hybrid learning environments, social media analytics, soft tissue, gamma correction, landmark detection, X-ray images, facial profile, prediction, artificial neural network, support vector machine, random forest, regression, offshore wave, wind speed, unmanned aerial vehicle, UAV smoke show, mobile networks, artificial intelligence, healthcare, database design, geospatial data, software, knowledge management, reasoning, information extraction, rule mining, knowledge acquisition, engineering, ontology, knowledge base, sustainable supplier selection, ontology population, knowledge acquisition from text, knowledge mining, drug–drug interaction, graph convolutional network, self-attention, deep learning, bic Book Industry Communication:K Economics, finance, business & management:KN Industry & industrial studies:KNT Media, information & communication industries:KNTX Information technology industries

File Description: application/octet-stream

Access URL: https://directory.doabooks.org/handle/20.500.12854/98891

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