Semantic Network

· Artificial Intelligence 第 64 冊 · One Billion Knowledgeable
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What Is Semantic Network

A knowledge base that depicts the semantic relations that exist between concepts in a network is known as a semantic network, also known as a frame network. This is a form of knowledge representation that is frequently put to use. It can be either directed or undirected and consists of vertices, which represent concepts, and edges, which reflect semantic relations between concepts, mapping or linking semantic fields. Vertices are used to represent concepts. Edges represent semantic interactions. A semantic network can be "instantiated" in a variety of different ways, such as a concept map or a graph database. Semantic triples are the typical way that typical standardized semantic networks are expressed.


How You Will Benefit


(I) Insights, and validations about the following topics:


Chapter 1: Semantic Network


Chapter 2: Knowledge Representation and Reasoning


Chapter 3: Semantic Web


Chapter 4: Ontology (Computer Science)


Chapter 5: John F. Sowa


Chapter 6: Conceptual Graph


Chapter 7: Semantic Similarity


Chapter 8: Semantic Research


Chapter 9: Semantic Data Model


Chapter 10: Knowledge Graph


(II) Answering the public top questions about semantic network.


(III) Real world examples for the usage of semantic network in many fields.


(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of semantic network' technologies.


Who This Book Is For


Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of semantic network.

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