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Semantic Memory
Semantic memory refers to general world knowledge that humans have accumulated throughout their lives. This general knowledge (word meanings, concepts, facts, and ideas) is intertwined in experience and dependent on culture. We can learn about new concepts by applying our knowledge learned from things in the past. Semantic memory is distinct from episodic memory, which is our memory of experiences and specific events that occur during our lives, from which we can recreate at any given point. For instance, semantic memory might contain information about what a cat is, whereas episodic memory might contain a specific memory of petting a particular cat. Semantic memory and episodic memory are both types of explicit memory (or declarative memory), that is, memory of facts or events that can be consciously recalled and "declared". The counterpart to declarative or explicit memory is nondeclarative memory or implicit memory. History The idea of semantic memory was first int ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Knowledge
Knowledge can be defined as awareness of facts or as practical skills, and may also refer to familiarity with objects or situations. Knowledge of facts, also called propositional knowledge, is often defined as true belief that is distinct from opinion or guesswork by virtue of justification. While there is wide agreement among philosophers that propositional knowledge is a form of true belief, many controversies in philosophy focus on justification: whether it is needed at all, how to understand it, and whether something else besides it is needed. These controversies intensified due to a series of thought experiments by Edmund Gettier and have provoked various alternative definitions. Some of them deny that justification is necessary and replace it, for example, with reliability or the manifestation of cognitive virtues. Others contend that justification is needed but formulate additional requirements, for example, that no defeaters of the belief are present or that ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Familiarity Effect
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Familiarity is knowledge, awareness or understanding of someone or something, such as facts, information, descriptions, or skills, which is acquired through experience or education by perceiving, discovering, or learning. It may also refer to: * Familiarity heuristic * Familiarity principle * Intimate relationship See also * Fame (other) Fame is the quality of being well-known and in the public eye. Celebrities are famous by definition. Fame may also refer to: Books * '' Fame: an art project'', a 2013 book and series of paintings by Robert Priseman * ''Fame'' (novel) (German ''R ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Matrix (mathematics)
In mathematics, a matrix (plural matrices) is a rectangular array or table of numbers, symbols, or expressions, arranged in rows and columns, which is used to represent a mathematical object or a property of such an object. For example, \begin1 & 9 & -13 \\20 & 5 & -6 \end is a matrix with two rows and three columns. This is often referred to as a "two by three matrix", a "-matrix", or a matrix of dimension . Without further specifications, matrices represent linear maps, and allow explicit computations in linear algebra. Therefore, the study of matrices is a large part of linear algebra, and most properties and operations of abstract linear algebra can be expressed in terms of matrices. For example, matrix multiplication represents composition of linear maps. Not all matrices are related to linear algebra. This is, in particular, the case in graph theory, of incidence matrices, and adjacency matrices. ''This article focuses on matrices related to linear algebra, an ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Semantic Relatedness
Semantic similarity is a metric defined over a set of documents or terms, where the idea of distance between items is based on the likeness of their meaning or semantic content as opposed to lexicographical similarity. These are mathematical tools used to estimate the strength of the semantic relationship between units of language, concepts or instances, through a numerical description obtained according to the comparison of information supporting their meaning or describing their nature. The term semantic similarity is often confused with semantic relatedness. Semantic relatedness includes any relation between two terms, while semantic similarity only includes "is a" relations. For example, "car" is similar to "bus", but is also related to "road" and "driving". Computationally, semantic similarity can be estimated by defining a topological similarity, by using ontologies to define the distance between terms/concepts. For example, a naive metric for the comparison of concepts ord ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Hebbian
Hebbian theory is a neuroscientific theory claiming that an increase in synaptic efficacy arises from a presynaptic cell's repeated and persistent stimulation of a postsynaptic cell. It is an attempt to explain synaptic plasticity, the adaptation of brain neurons during the learning process. It was introduced by Donald Hebb in his 1949 book '' The Organization of Behavior.'' The theory is also called Hebb's rule, Hebb's postulate, and cell assembly theory. Hebb states it as follows: Let us assume that the persistence or repetition of a reverberatory activity (or "trace") tends to induce lasting cellular changes that add to its stability. ... When an axon of cell ''A'' is near enough to excite a cell ''B'' and repeatedly or persistently takes part in firing it, some growth process or metabolic change takes place in one or both cells such that ''A''’s efficiency, as one of the cells firing ''B'', is increased. The theory is often summarized as "Cells that fire together wire toge ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Association (psychology)
Association in psychology refers to a mental connection between concepts, events, or mental states that usually stems from specific experiences.Klein, Stephen (2012). ''Learning: Principles and Applications'' (6 ed.). SAGE Publications. . Associations are seen throughout several schools of thought in psychology including behaviorism, associationism, psychoanalysis, social psychology, and structuralism. The idea stems from Plato and Aristotle, especially with regard to the succession of memories, and it was carried on by philosophers such as John Locke, David Hume, David Hartley, and James Mill.Boring, E. G. (1950) It finds its place in modern psychology in such areas as memory, learning, and the study of neural pathways. Learned associations Associative learning is when a subject creates a relationship between stimuli (e.g. auditory or visual) or behavior and the original stimulus. The higher the concreteness of stimulus items, the more likely are they to evoke ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Semantic Feature-comparison Model
The semantic feature comparison model is used "to derive predictions about categorization times in a situation where a subject must rapidly decide whether a test item is a member of a particular target category".Smith, E. E., Shoben. E. J., and Rips, L. J. (1974). Structure and Process in Semantic Memory: A Feature Model for Semantic Decisions. Psychological Review, 81(3), 214–241. In this semantic model, there is an assumption that certain occurrences are categorized using its features or attributes of the two subjects that represent the part and the group. A statement often used to explain this model is "a robin is a bird". The meaning of the words ''robin'' and ''bird'' are stored in the memory by virtue of a list of features which can be used to ultimately define their categories, although the extent of their association with a particular category varies. History This model was conceptualized by Edward Smith, Edward Shoben and Lance Rips in 1974 after they derived various obs ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Artificial Intelligence
Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by animals and humans. Example tasks in which this is done include speech recognition, computer vision, translation between (natural) languages, as well as other mappings of inputs. The ''Oxford English Dictionary'' of Oxford University Press defines artificial intelligence as: the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. AI applications include advanced web search engines (e.g., Google), recommendation systems (used by YouTube, Amazon and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g., Tesla), automated decision-making and competing at the highest level in strategic game systems (such as chess and Go). ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Comprehension (logic)
In logic, the comprehension of an object is the totality of intensions, that is, attributes, characters, marks, properties, or qualities, that the object possesses, or else the totality of intensions that are pertinent to the context of a given discussion. This is the correct technical term for the whole collection of intensions of an object, but it is common in less technical usage to see 'intension' used for both the composite and the primitive ideas. See also * Extension * Extensional definition * Intension * Intensional definition In logic, extensional and intensional definitions are two key ways in which the objects, concepts, or referents a term refers to can be defined. They give meaning or denotation to a term. Intensional definition An intensional definition gives ... Concepts in logic Definition {{Logic-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Logic
Logic is the study of correct reasoning. It includes both formal and informal logic. Formal logic is the science of deductively valid inferences or of logical truths. It is a formal science investigating how conclusions follow from premises in a topic-neutral way. When used as a countable noun, the term "a logic" refers to a logical formal system that articulates a proof system. Formal logic contrasts with informal logic, which is associated with informal fallacies, critical thinking, and argumentation theory. While there is no general agreement on how formal and informal logic are to be distinguished, one prominent approach associates their difference with whether the studied arguments are expressed in formal or informal languages. Logic plays a central role in multiple fields, such as philosophy, mathematics, computer science, and linguistics. Logic studies arguments, which consist of a set of premises together with a conclusion. Premises and conclusions are usual ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Discourse Analysis
Discourse analysis (DA), or discourse studies, is an approach to the analysis of written, vocal, or sign language use, or any significant semiotic event. The objects of discourse Analysis ( discourse, writing, conversation, communicative event) are variously defined in terms of coherent sequences of sentences, propositions, speech acts, speech, or Conversation Analysis#Turn-taking organization, turns-at-talk. Contrary to much of traditional linguistics, discourse analysts not only study language use 'beyond the sentence boundary' but also prefer to analyze 'naturally occurring' language use, not invented examples. Text linguistics is a closely related field. The essential difference between discourse analysis and text linguistics is that discourse analysis aims at revealing social psychology (sociology), socio-psychological characteristics of a person/persons rather than text structure. Discourse analysis has been taken up in a variety of disciplines in the humanities and so ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Neural Network
A neural network is a network or neural circuit, circuit of biological neurons, or, in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus, a neural network is either a biological neural network, made up of biological neurons, or an artificial neural network, used for solving artificial intelligence (AI) problems. The connections of the biological neuron are modeled in artificial neural networks as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed. This activity is referred to as a linear combination. Finally, an activation function controls the amplitude of the output. For example, an acceptable range of output is usually between 0 and 1, or it could be −1 and 1. These artificial networks may be used for predictive modeling, adaptive control and applications where they can be trained via a dataset. Self-learning re ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |