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A semantic network, or frame network is a knowledge base that represents semantic relations between concepts in a network. This is often used as a form of knowledge representation . It is a directed or undirected graph consisting of vertices , which represent concepts , and edges , which represent semantic relations between concepts , [ 1 ...
In Artificial Intelligence, Donetsk, "Nauka i obrazovanie" Institute of Artificial Intelligence, Ukraine, 2004, No 3. P. 598-606 Shuklin D.E. The Structure of a Semantic Neural Network Extracting the Meaning from a Text, In Cybernetics and Systems Analysis, Volume 37, Number 2, 4 March 2001, pp. 182–186(5) [1]
Many of the early approaches to knowledge represention in Artificial Intelligence (AI) used graph representations and semantic networks, similar to knowledge graphs today. In such approaches, problem solving was a form of graph traversal [2] or path-finding, as in the A* search algorithm. Typical applications included robot plan-formation and ...
Symbolic AI used tools such as logic programming, production rules, semantic nets and frames, and it developed applications such as knowledge-based systems (in particular, expert systems), symbolic mathematics, automated theorem provers, ontologies, the semantic web, and automated planning and scheduling systems.
For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...
Frames are the primary data structure used in artificial intelligence frame languages; they are stored as ontologies of sets. Frames are also an extensive part of knowledge representation and reasoning schemes. They were originally derived from semantic networks and are therefore part of structure-based knowledge representations.
In machine learning, semantic analysis of a text corpus is the task of building structures that approximate concepts from a large set of documents. It generally does not involve prior semantic understanding of the documents. Semantic analysis strategies include: Metalanguages based on first-order logic, which can analyze the speech of humans.
Spaun ("Semantic Pointer Architecture Unified Network") is a cognitive architecture pioneered by Chris Eliasmith of the University of Waterloo Centre for Theoretical Neuroscience. [1] It consists of 2.5 million simulated neurons organized into subsystems that resemble specific brain regions, such as the prefrontal cortex , basal ganglia , and ...