Conceptual Blending And Computer Metaphor

The term "metaphor" is used here not in a narrow linguistic sense, but in the sense of rich and complex cognitive models.According to Lakoff and Johnson, a metaphoric cognitive model is a way to structure the knowledge of one domain by mapping onto it concepts and relations from an existing domain that is already familiar. Metaphor in this sense is not a mere linguistic device used only for the figurative embellishment of language, but a fundamental way of learning and structuring conceptual systems, a part of everyday discourse.We pursue here our exploration of Conceptual Blending-a ubiquitous cognitive mechanism-and of the "many-space" model, of which the standard "two-domain" model is a collateral feature or special case of many space model. The many-space model assigns roles to the two input spaces (Source and Target in Conceptual Metaphor Theory), but also to two middle spaces-a generic space-which contains skeletal structure that applies to both input spaces and a blended space which is a rich space integrating in a partial fashion specific structures from both of the input spaces. The blended space often contains structures not projected to it from either input space. The relationship among these four spaces, and the mechanism of conceptual projection among them, are intricate, going beyond any of the mechanisms that have been proposed in previously model. This introduces a higher degree of variability and a loss of parsimony, but with a corresponding increase in dynamics, sensibility and generality. Conceptual Blending is not a compositional algorithmic process and cannot be modeled as such for even the most rudimentary cases. Blends are not predictable solely from the structure of the inputs. Rather, they are highly motivated by such structure, in harmony with independently available background and contextual structure; they comply with competing optimality constraints, and with locally relevant functional goals.In this study, we examine the application and implication of conceptual integration in newly created jargons used in computer. The analyses are based on a rich array of attested data in ordinary language in computer. We conclude this is a process of blending at the level of expression; the jargon in computer is mostly metaphorical; blending is integral in our construction of concept and indispensable in computer reasoning. Because Conceptual Blending is an unrivaled tool of compression and fusion of selective structures from input spaces and because of the emergence of some thing new, presumably a result of integrating certain aspects of the parts, these frequently used appropriate and apt terms are the result of blending process. Meanwhile the conceptual blending is particularly apt at explaining novel and complex metaphor-like phenomena, such as those which require projection from more than one input to the output.What's more, we are well aware of metaphor in the reasoning and operation of computer, but the role of unconscious blending process in these activities, and hi the construction of the metaphors they use and develop, has gone unnoticed. In everyday life, the creativity is hidden by the largely unconscious and extremely swift nature of the myriad cognitive operations that enter into the simplest of our meaning constructions. This reveals that the blending process is unconscious, obtainable only after analysis.Further, Blending operates to produce understandings of metaphorical expressions. Any expression in language (including literal) is a way of prompting hearer and reader to assemble and develop conceptual constructions, including blends. The conceptual blending is the hidden engine that constructs the conceptual edifices. Language is only the tip of a spectacular cognitive iceberg. We conclude the jargon in computer is mostly metaphorical; blending is integral in our construction of concept and indispensable hi computer reasoning.