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Beskrivning
Although many representation models or cognitive models have been proposed, such as expert systems or knowledge graphs, they cannot represent procedural knowledge, i.e., dynamic knowledge, in an efficient way.This book introduces a new knowledge representation model called MDATA (Multi-dimensional Data Association and inTelligent Analysis).
Introduction to the MDATA Model.- The Framework of the MDATA Computing Model.- Spatiotemporal Data Cleaning and Knowledge Fusion.- Chinese Named Entity Recognition: Applications and Challenges.- Joint Extraction of Entities and Relations: An Advanced BERT-based Decomposition Method.- Entity Alignment: Optimization by Seed Selection.- Knowledge Extraction: Automatic Classification of Matching Rules.- Network Embedding Attack: An Euclidean Distance based Method.- Few-Shot Knowledge Reasoning: An Attention Mechanism based Method.- Applications of Knowledge Representation Learning.- Detection and Defense Methods of Cyber Attacks.- A Distributed Framework for APT Attack Analysis.- Social Unrest Events Prediction by Contextual Gated Graph Convolutional Networks.- Information Cascading in Social Networks.