Semantic feature-comparison model

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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". [1] 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.

A prediction, or forecast, is a statement about a future event. A prediction is often, but not always, based upon experience or knowledge. There is no universal agreement about the exact difference between the two terms; different authors and disciplines ascribe different connotations.

Categorization is the process in which ideas and objects are recognized, differentiated, and understood. Categorization implies that objects are grouped into categories, usually for some specific purpose. Ideally, a category illuminates a relationship between the subjects and objects of knowledge. Categorization is fundamental in language, prediction, inference, decision making and in all kinds of environmental interaction. It is indicated that categorization plays a major role in computer programming.

European robin species of bird

The European robin, known simply as the robin or robin redbreast in the British Isles, is a small insectivorous passerine bird, specifically a chat, that was formerly classified as a member of the thrush family (Turdidae) but is now considered to be an Old World flycatcher. About 12.5–14.0 cm (5.0–5.5 inches) in length, the male and female are similar in colouration, with an orange breast and face lined with grey, brown upperparts and a whitish belly. It is found across Europe, east to Western Siberia and south to North Africa; it is sedentary in most of its range except the far north.

Contents

History

This model was conceptualized by Edward Smith, Edward Shoben and Lance Rips in 1974 after they derived various observations from semantic verification experiments conducted at the time. Respondents merely have to answer "true" or "false" to given sentences. Out of these experiments, they observed that people respond faster when (1) statements are true, (2) nouns are members of smaller categories, (3) items are "typical" or commonly associated with the category (also called prototypes), and (4) items are primed by a similar item previously given (University of Alaska Anchorage, n.d.). In the latter item, respondents will respond faster to the latter statement since the category bird has been primed. Based on the previous observations, the proponents were able to come up with the semantic feature comparison model. [1]

University of Alaska Anchorage university

The University of Alaska Anchorage (UAA) is a public research university located in Anchorage, Alaska. UAA also administers four community campuses spread across Southcentral Alaska. These include Kenai Peninsula College, Kodiak College, Matanuska–Susitna College, and Prince William Sound College. Between the community campuses and the main Anchorage campus, over 20,000 undergraduate, graduate, and professional students are currently enrolled at UAA. This makes it the largest institution of higher learning in the University of Alaska System, as well as the state.

Theory

The cognitive approach consists of two concepts: information processing depends on internal representations, and that mental representations undergo transformations. For the first concept, we could describe an object in a number of ways, with drawings, equations, or verbal descriptions, but it is up to the recipient to have a background understanding of the context to which the object is being described in order to fully comprehend the deliverable. The second concept explains how memory can alter the way we perceive representations of something, by determining the sequence in which the information is processed based on previous experiences.

Information processing is the change (processing) of information in any manner detectable by an observer. As such, it is a process that describes everything that happens (changes) in the universe, from the falling of a rock to the printing of a text file from a digital computer system. In the latter case, an information processor is changing the form of presentation of that text file. Information processing may more specifically be defined in terms used by, Claude E. Shannon as the conversion of latent information into manifest information. Latent and manifest information is defined through the terms of equivocation, dissipation, and transformation.

A mental representation, in philosophy of mind, cognitive psychology, neuroscience, and cognitive science, is a hypothetical internal cognitive symbol that represents external reality, or else a mental process that makes use of such a symbol: "a formal system for making explicit certain entities or types of information, together with a specification of how the system does this".

Features

The main features of the model, as discussed by Smith et al. (1974), are the defining features and the characteristic features. Defining features refer to the characteristics that are essential elements of the category, the non-negotiable, so to speak. For example, the 'bird' category includes such defining features as 'they have wings', 'feathers', 'they lay eggs', etc. Characteristic features refer to the elements usually found or inherent to category members but are not found in all, or non-essentials. For example, birds 'fly', – that is characteristic because while most birds fly, there are some who cannot.

The model has two stages for decision making. First, all features of the two concepts (bird and robin, in our example) are compared to find out how alike they are. If the decision is that they are very similar or very dissimilar, then a true or false decision can be made. Second, if the characteristics/features are in-between then the focus shifts to the defining features in order to decide if the example possesses enough features of the category, thus, categorization depends on similarity and not on the size of the category.

Similarity refers to the psychological nearness or proximity of two mental representations. Research in cognitive psychology has taken a number of approaches to the concept of similarity. Each of them is related to a particular set of assumptions about knowledge representation.

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Concept mental representation or an abstract object or an ability

Concepts are mental representations, abstract objects or abilities that make up the fundamental building blocks of thoughts and beliefs. They play an important role in all aspects of cognition.

Short-term memory is the capacity for holding, but not manipulating, a small amount of information in mind in an active, readily available state for a short period of time. For example, short-term memory can be used to remember a phone number that has just been recited. The duration of short-term memory is believed to be in the order of seconds. The most commonly cited capacity is The Magical Number Seven, Plus or Minus Two, despite the fact that Miller himself stated that the figure was intended as "little more than a joke" and that Cowan (2001) provided evidence that a more realistic figure is 4±1 units. In contrast, long-term memory can hold the information indefinitely.

Semantics is the linguistic and philosophical study of meaning, in language, programming languages, formal logics, and semiotics. It is concerned with the relationship between signifiers—like words, phrases, signs, and symbols—and what they stand for in reality, their denotation.

Semantic network knowledge representation scheme that uses a directed graph to encode knowledge

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.

Semantic memory is one of the two types of declarative or explicit memory. Semantic memory refers to general world knowledge that we have accumulated throughout our lives. This general knowledge is intertwined in experience and dependent on culture. 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. We can learn about new concepts by applying our knowledge learned from things in the past. The counterpart to declarative or explicit memory is nondeclarative memory or implicit memory.

In cognitive psychology, chunking is a process by which individual pieces of information are bound together into a meaningful whole. A chunk is defined as a familiar collection of more elementary units that have been inter-associated and stored in memory repeatedly and act as a coherent, integrated group when retrieved.

Prototype theory is a mode of graded categorization in cognitive science, where some members of a category are more central than others. For example, when asked to give an example of the concept furniture, chair is more frequently cited than, say, stool. Prototype theory has also been applied in linguistics, as part of the mapping from phonological structure to semantics.

Cognitive semantics is part of the cognitive linguistics movement. Semantics is the study of linguistic meaning. Cognitive semantics holds that language is part of a more general human cognitive ability, and can therefore only describe the world as people conceive of it. It is implicit that different linguistic communities conceive of simple things and processes in the world differently, not necessarily some difference between a person's conceptual world and the real world.

In linguistics, a feature is the assignment of binary or unary conditions which act as constraints.

Associative visual agnosia agnosia that is a loss of the ability to recognize visual scenes or classes of objects but retain the abilty to describe them

Associative visual agnosia is a form of visual agnosia. It is an impairment in recognition or assigning meaning to a stimulus that is accurately perceived and not associated with a generalized deficit in intelligence, memory, language or attention. The disorder appears to be very uncommon in a "pure" or uncomplicated form and is usually accompanied by other complex neuropsychological problems due to the nature of the etiology. Afflicted individuals can accurately distinguish the object, as demonstrated by the ability to draw a picture of it or categorize accurately, yet they are unable to identify the object, its features or its functions.

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Concept learning, also known as category learning, concept attainment, and concept formation, is defined by Bruner, Goodnow, & Austin (1967) as "the search for and listing of attributes that can be used to distinguish exemplars from non exemplars of various categories". More simply put, concepts are the mental categories t help nts, or ideas, building on the understanding that each object, vent, or idea has a set of co evant features. Thus, concept learning is a strategy which requires a learner to compare and contrast roups or categories that contain concept-relevant features with groups or categories that do not contain concept-relevant fea learning task in which a human or machine learner is trained to classify objects by being shown a set of example objects along with their class labels. The learner simplifies what has been observed by condensing it in the form of an example. This simplified version of what has been learned is then applied to future examples. Concept learning may be simple or complex because learning takes place over many areas. When a concept is difficult, it is less likely that the learner will be able to simplify, and therefore will be less likely to learn. Colloquially, the task is known as learning from examples. Most theories of concept learning are based on the storage of exemplars and avoid summarization or overt abstraction of any kind.

In psycholinguistics, language production is the production of spoken or written language. It describes all of the stages between having a concept, and translating that concept into linguistic form. In computational linguistics/natural language processing and artificial intelligence, the term natural language generation (NLG) is more common, and those models may or may not be psychologically motivated.

Memory is the process of storing and recalling information that was previously acquired. Memory is occurs through three fundamental stages: encoding, storage, and retrieval. Storing refers to the process of placing newly acquired information into memory, which is modified in the brain for easier storage. Encoding this information makes the process of retrieval easier for the brain where it can be recalled and brought into conscious thinking. Modern memory psychology differentiates between the two distinct types of memory storage: short-term memory and long-term memory. Several models of memory have been proposed over the past century, some of them suggesting different relationships between short- and long-term memory to account for different ways of storing memory.

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Object recognition is the ability to perceive an object's physical properties and apply semantic attributes to it. This process includes the understanding of its use, previous experience with the object, and how it relates to others. Regardless of an object's position or illumination, humans possess the ability to effectively identify and label an object. Humans are one of the few species that possess the ability of invariant visual object recognition. Both "front end" and "back end" processing are required for a species to be able to recognize objects at varying distances, angles, lighting, etc....

Fuzzy-trace theory (FTT) is a theory of cognition originally proposed by Charles Brainerd and Valerie F. Reyna that draws upon dual-trace conceptions to predict and explain cognitive phenomena, particularly in the memory and reasoning domains. The theory has been used in areas such as cognitive psychology, human development, and social psychology to explain, for instance, false memory and its development, probability judgments, medical decision making, risk perception and estimation, and biases and fallacies in decision making.

Exemplar theory is a proposal concerning the way humans categorize objects and ideas in psychology. It argues that individuals make category judgments by comparing new stimuli with instances already stored in memory. The instance stored in memory is the "exemplar". The new stimulus is assigned to a category based on the greatest number of similarities it holds with exemplars in that category. For example, the model proposes that people create the "bird" category by maintaining in their memory a collection of all the birds they have experienced: sparrows, robins, ostriches, penguins, etc. If a new stimulus is similar enough to some of these stored bird examples, the person categorizes the stimulus in the "bird" category. Various versions of the exemplar theory have led to a simplification of thought concerning concept learning, because they suggest that people use already-encountered memories to determine categorization, rather than creating an additional abstract summary of representations.

Cognitive computing (CC) describes technology platforms that, broadly speaking, are based on the scientific disciplines of artificial intelligence and signal processing. These platforms encompass machine learning, reasoning, natural language processing, speech recognition and vision, human–computer interaction, dialog and narrative generation, among other technologies.

References

  1. 1 2 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.