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Spreading Activation
Spreading activation is a method for searching associative networks, biological and artificial neural networks, or semantic networks.Fähndrich, J. (2018). Semantic decomposition and marker passing in an artificial representation of meaning. Technische Universitaet Berlin (Germany)/ref> The search process is initiated by labeling a set of source nodes (e.g. concepts in a semantic network) with weights or "activation" and then iteratively propagating or "spreading" that activation out to other nodes linked to the source nodes. Most often these "weights" are real values that decay as activation propagates through the network. When the weights are discrete this process is often referred to as marker passing. Activation may originate from alternate paths, identified by distinct markers, and terminate when two alternate paths reach the same node. However brain studies show that several different brain areas play an important role in semantic processing.Karalyn Patterson, Peter J. Nesto ...
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Biological Neural Network
A neural network, also called a neuronal network, is an interconnected population of neurons (typically containing multiple neural circuits). Biological neural networks are studied to understand the organization and functioning of nervous systems. Closely related are artificial neural networks, machine learning models inspired by biological neural networks. They consist of artificial neurons, which are mathematical functions that are designed to be analogous to the mechanisms used by neural circuits. Overview A biological neural network is composed of a group of chemically connected or functionally associated neurons. A single neuron may be connected to many other neurons and the total number of neurons and connections in a network may be extensive. Connections, called synapses, are usually formed from axons to dendrites, though dendrodendritic synapses and other connections are possible. Apart from electrical signalling, there are other forms of signalling that arise from n ...
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Artificial Neural Networks
In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a computational model inspired by the structure and functions of biological neural networks. A neural network consists of connected units or nodes called '' artificial neurons'', which loosely model the neurons in the brain. Artificial neuron models that mimic biological neurons more closely have also been recently investigated and shown to significantly improve performance. These are connected by ''edges'', which model the synapses in the brain. Each artificial neuron receives signals from connected neurons, then processes them and sends a signal to other connected neurons. The "signal" is a real number, and the output of each neuron is computed by some non-linear function of the sum of its inputs, called the '' activation function''. The strength of the signal at each connection is determined by a ''weight'', which adjusts during the learning process. Typically, neur ...
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Semantic Network
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, mapping or connecting semantic fields. A semantic network may be instantiated as, for example, a graph database or a concept map. Typical standardized semantic networks are expressed as semantic triples. Semantic networks are used in natural language processing applications such as semantic parsing and word-sense disambiguation. Semantic networks can also be used as a method to analyze large texts and identify the main themes and topics (e.g., of social media posts), to reveal biases (e.g., in news coverage), or even to map an entire research field. History Examples of the use of semantic networks in logic, directed acyclic graphs as a mnemonic ...
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Semantic Processing
In psycholinguistics, semantic processing is the stage of language processing that occurs after one hears a word and encodes its meaning: the mind relates the word to other words with similar meanings. Once a word is perceived, it is placed in a context mentally that allows for a deeper processing. Therefore, semantic processing produces memory traces that last longer than those produced by shallow processing, since shallow processing produces fragile memory traces that decay rapidly. Proper semantic cognition requires 1) knowledge about the item/word and its features or associations, 2) retrieving the proper information that fits one's current goals and situation. For example, if one saw a sign while driving that said “fork in the road ahead” they should be able to inhibit a strong association (e.g., silverware), and retrieve a distant association that is more relevant meaning (e.g., road structures). Semantic processing is the deepest level of processing and it require ...
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Cognitive Psychology
Cognitive psychology is the scientific study of human mental processes such as attention, language use, memory, perception, problem solving, creativity, and reasoning. Cognitive psychology originated in the 1960s in a break from behaviorism, which held from the 1920s to 1950s that unobservable mental processes were outside the realm of empirical science. This break came as researchers in linguistics and cybernetics, as well as applied psychology, used models of mental processing to explain human behavior. Work derived from cognitive psychology was integrated into other branches of psychology and various other modern disciplines like cognitive science, linguistics, and economics. History Philosophically, ruminations on the human mind and its processes have been around since the times of the Ancient Greece, ancient Greeks. In 387 BCE, Plato had suggested that the brain was the seat of the mental processes. In 1637, René Descartes posited that humans are born with innate ideas and ...
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Information Retrieval
Information retrieval (IR) in computing and information science is the task of identifying and retrieving information system resources that are relevant to an Information needs, information need. The information need can be specified in the form of a search query. In the case of document retrieval, queries can be based on full-text search, full-text or other content-based indexing. Information retrieval is the science of searching for information in a document, searching for documents themselves, and also searching for the metadata that describes data, and for databases of texts, images or sounds. Automated information retrieval systems are used to reduce what has been called information overload. An IR system is a software system that provides access to books, journals and other documents; it also stores and manages those documents. Web search engines are the most visible IR applications. Overview An information retrieval process begins when a user enters a query into the sys ...
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Connectionism
Connectionism is an approach to the study of human mental processes and cognition that utilizes mathematical models known as connectionist networks or artificial neural networks. Connectionism has had many "waves" since its beginnings. The first wave appeared 1943 with Warren Sturgis McCulloch and Walter Pitts both focusing on comprehending neural circuitry through a formal and mathematical approach, and Frank Rosenblatt who published the 1958 paper "The Perceptron: A Probabilistic Model For Information Storage and Organization in the Brain" in ''Psychological Review'', while working at the Cornell Aeronautical Laboratory. The first wave ended with the 1969 book about the limitations of the original perceptron idea, written by Marvin Minsky and Seymour Papert, which contributed to discouraging major funding agencies in the US from investing in connectionist research. With a few noteworthy deviations, most connectionist research entered a period of inactivity until the mid-1980 ...
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Semantics
Semantics is the study of linguistic Meaning (philosophy), meaning. It examines what meaning is, how words get their meaning, and how the meaning of a complex expression depends on its parts. Part of this process involves the distinction between sense and reference. Sense is given by the ideas and concepts associated with an expression while reference is the object to which an expression points. Semantics contrasts with syntax, which studies the rules that dictate how to create grammatically correct sentences, and pragmatics, which investigates how people use language in communication. Lexical semantics is the branch of semantics that studies word meaning. It examines whether words have one or several meanings and in what lexical relations they stand to one another. Phrasal semantics studies the meaning of sentences by exploring the phenomenon of compositionality or how new meanings can be created by arranging words. Formal semantics (natural language), Formal semantics relies o ...
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Psycholinguistics
Psycholinguistics or psychology of language is the study of the interrelation between linguistic factors and psychological aspects. The discipline is mainly concerned with the mechanisms by which language is processed and represented in the mind and brain; that is, the psychology, psychological and neurobiology, neurobiological factors that enable humans to acquire, use, comprehend, and produce language. Psycholinguistics is concerned with the cognitive faculties and processes that are necessary to produce the grammatical constructions of language. It is also concerned with the perception of these constructions by a listener. Initial forays into psycholinguistics were in the philosophical and educational fields, mainly due to their location in departments other than applied sciences (e.g., cohesive data on how the human brain functioned). Modern research makes use of biology, neuroscience, cognitive science, linguistics, and information science to study how the mind-brain process ...
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Memory
Memory is the faculty of the mind by which data or information is encoded, stored, and retrieved when needed. It is the retention of information over time for the purpose of influencing future action. If past events could not be remembered, it would be impossible for language, relationships, or personal identity to develop. Memory loss is usually described as forgetfulness or amnesia. Memory is often understood as an informational processing system with explicit and implicit functioning that is made up of a sensory processor, short-term (or working) memory, and long-term memory. This can be related to the neuron. The sensory processor allows information from the outside world to be sensed in the form of chemical and physical stimuli and attended to various levels of focus and intent. Working memory serves as an encoding and retrieval processor. Information in the form of stimuli is encoded in accordance with explicit or implicit functions by the working memory p ...
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Artificial Intelligence
Artificial intelligence (AI) is the capability of computer, computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of research in computer science that develops and studies methods and software that enable machines to machine perception, perceive their environment and use machine learning, learning and intelligence to take actions that maximize their chances of achieving defined goals. High-profile applications of AI include advanced web search engines (e.g., Google Search); recommendation systems (used by YouTube, Amazon (company), Amazon, and Netflix); virtual assistants (e.g., Google Assistant, Siri, and Amazon Alexa, Alexa); autonomous vehicles (e.g., Waymo); Generative artificial intelligence, generative and Computational creativity, creative tools (e.g., ChatGPT and AI art); and Superintelligence, superhuman play and analysis in strategy games (e.g., ...
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