深層学習:Deep Learning

Similarity in global matching (3) Matching graph patterns by iterative computation

Natural language similarity for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) applications. Graph data matching calculations for ontology similarity extraction.

2021.08.14

セマンテックウェブ技術:Semantic web Technology推論技術:inference Technology検索技術:Search Technology機械学習:Machine Learning深層学習:Deep Learning自然言語処理:Natural Language Processing

Protected: Graph Neural Networks (1) Overview

An overview of machine learning using graph neural networks for use in digital transformation (DX) and artificial intelligence (AI). On graph convolutional algorithms for chemical combination and natural language processing.

2021.08.10

機械学習:Machine Learning深層学習:Deep Learning

Similarity in global matching (2) Similarity of Mereological Graph Patterns

Natural Language Similarity for Digital Transformation (DX), Artificial Intelligence (AI), and Machine Learning (ML) Applications. Similarity evaluation of ontologies by relational pattern matching.

2021.07.15

セマンテックウェブ技術:Semantic web Technology推論技術:inference Technology検索技術:Search Technology機械学習:Machine Learning深層学習:Deep Learning自然言語処理:Natural Language Processing

Similarity in global matching (1) Overview

Similarity of natural language for the use of digital transformation (DX), artificial intelligence (AI), and machine learning (ML), and similarity of ontology as matching of graph patterns.

2021.07.14

推論技術:inference Technology検索技術:Search Technology機械学習:Machine Learning深層学習:Deep Learning自然言語処理:Natural Language Processing

Basic Similarity(5) Data Expansion Techniques

Natural Language Similarity for Digital Transformation (DX), Artificial Intelligence (ML), Machine Learning (ML). Similarity for ontology matching using an extended data approach.

2021.07.13

セマンテックウェブ技術:Semantic web Technology推論技術:inference Technology検索技術:Search Technology機械学習:Machine Learning深層学習:Deep Learning自然言語処理:Natural Language Processing

Basic Similarity (4) Internal structure-based approach

Similarity estimation of natural language for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) applications based on data types and domain elements.

2021.07.12

推論技術:inference Technology検索技術:Search Technology機械学習:Machine Learning深層学習:Deep Learning自然言語処理:Natural Language Processing

Basic Similarity (2) String-based approach

Summary of various methods for structuring raw text as a basis for natural language processing for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) applications, normalization techniques, substring handling, edit distance, token-based Distance and path comparison

2021.07.08

推論技術:inference Technology検索技術:Search Technology機械学習:Machine Learning深層学習:Deep Learning自然言語処理:Natural Language Processing

Protected: Bayesian Deep Learning – Introduction

Overview of Bayesian deep models, an evolution of deep learning and probabilistic generative models.

2021.05.25

アルゴリズム:Algorithms機械学習:Machine Learning深層学習:Deep Learning確率・統計:Probability and Statistics

Protected: An overview of the expert integration problem in online forecasting and its implementation in Regret

Overview of online predictive learning for solving sequential prediction problems, introduction to Regret

2021.05.22

推論技術:inference Technology最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning確率・統計:Probability and Statistics

Protected: Reinforcement Learning Overview

An overview of reinforcement learning for learning sequential decision rules

2021.05.20

アルゴリズム:Algorithms最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning