機械学習:Machine Learning

Protected: Topic models that capture the individuality of language

Topic models to capture latent meanings behind sentences, differences between various probabilistic approaches and deep learning, supervised LDA, Boltzmann machines,Naive Bayes
確率・統計:Probability and Statistics

Introduction to models of language (probabilistic unigram models and Bayesian probability)

Natural language processing as it applies to digital transformation (DX), artificial intelligence (AI), machine learning, etc. Modeling of natural language, application of unigram models and Bayesian probabilistic models.
セマンテックウェブ技術:Semantic web Technology

Strategies in similarity matching methods (7) Improved alignment disambiguation

Alignment disambiguation for optimization of natural language simirality and ontology matching for digital transformation (DX) and artificial intelligence (AI) applications
セマンテックウェブ技術:Semantic web Technology

Strategies in similarity matching methods (6) Alignment extraction approach

Optimization and alignment extraction for natural language simirality and ontology matching for digital transformation (DX) and artificial intelligence (AI) applications
セマンテックウェブ技術:Semantic web Technology

Strategies in similarity matching methods (5) Tuning approaches

Digital transformation (DX), similarity of natural language for artificial intelligence (AI), tuning by machine learning for ontology matching, stacked generalization, genetic algorithms
セマンテックウェブ技術:Semantic web Technology

Strategies in similarity matching methods (4) Learning to sort alignments

Digital transformation (DX), simirality of natural language for artificial intelligence (AI) applications, sorting alignment by machine learning for ontology matching, SVM, decision trees, WHIRL, neural nets, naive Bayes
セマンテックウェブ技術:Semantic web Technology

Strategies in similarity matching methods (3) Weighted selection approach

Natural language similarity for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) applications. Similarity evaluation, matching strategies, and weighting strategies for ontologies using relational pattern matching.
セマンテックウェブ技術:Semantic web Technology

Strategies in similarity matching methods (2) Context-based approach

Natural language similarity for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) applications. Similarity evaluation of ontologies by relational pattern matching, matching strategies, context-based matching.
セマンテックウェブ技術:Semantic web Technology

Strategies in similarity matching methods (1) Overview

Natural language similarity for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) applications. Similarity evaluation of ontologies by relational pattern matching, matching strategies.
セマンテックウェブ技術:Semantic web Technology

Similarity in global matching(6) Semantic approach

Natural language similarity for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) applications. Similarity evaluation of ontologies by relational pattern matching, semantic approach, SAT solver, description logic.
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