Conceptual Blending and Computer Metaphor

【作者】 覃胜勇；

【导师】 刘正光；

【作者基本信息】 湖南大学 ， 外国语言学及应用语言学， 2002， 硕士

【摘要】 自莱克夫(George Lakoff)发表《我们赖以生存的隐喻》(Metaphor We Live By)以来，隐喻从传统的修辞学范畴中摆脱出来，已被看作是人类所具有的一种认知机制。经过比较，我们发现概念隐喻理论(Conceptual Metaphor)可以包括在概念整合(Conceptual Integration或Conceptual Blending)，人类这一普遍(general)、动态(dynamic)、在线(on-line)、易适应(supple)、强大的认知机制框架之下。由于概念整合网络模式(Network Model)的各种优化原则或限制参数(Optimality Principle或Parameters)的作用，概念整合网络的动态运作产生五个典型网络模式，即SimplexNetworks，Mirror Networks，Single-scope Networks，Double-scope、with MetonymicProjection和Double-Scope Networks，因而从Literal Language 到 Figurative Language的渐进过渡(continuum)可以得到比较完美的解释，为将语言划分为LiteralLanguage和Figurative Language的二分法(dichotomy)提供了反证。同理，这一模型也可以解决隐喻的固化度(entrenchment)问题，即新鲜程度(Degree of Novelty)，从Dead Metaphor或Dormant Metaphor到Live Metaphor或Novel Metaphor也存在一个过渡体。概念隐喻理论主要探讨固化度高的传统隐喻(ConventionalMetaphor)，概念整和不仅为传统隐喻，也为新创隐喻(Novel Metaphor)提供了完美的解释。传统的靶域到源域的固化映射隐喻的原型就是单范围网络(Single-scope Networks)。计算机科学发展迅速，新的应用，新的软件，新的硬件不断地开发出来。本文并不探讨计算机科学本身，而是研究计算机行业新出现的词语，如信息高速公路(informationhighway)、病毒(virus)、桌面(desktop)、视窗(windows)、赛伯空间(cyberspace)、电子邮件(electronic mail)、鼠标(mouse)这些有代表性的词语(新创隐喻)。这些隐喻性的命名方式和意义建构反映了我们的概念整合过程，而这一过程是在无意识(unconscious)的情况下发生的。不经过分析，我们无从得知。由于无意识，所以我们就习以为常，并不深究。本文的实例研究有助于我们认识这一事实上无处不在(ubiquitous)的认知操作过程。我们很清楚隐喻在计算机人机界面、软件、硬件、网络中的作用，隐喻使我们很容易就了解、掌握，并使用这些 新兴事物。但概念整合，这一已被证明是人类普遍的认知机制，在这些隐喻以及 这些隐喻意义的建构中的重要作用却不为我们注意。经过分析，发现这些隐喻性 表达方式都涉及到二个以上的心理空间的认知运作，经过一系列的结构映射 （StrUC’tUr P呐ection）和整合过程，产生了一个突变结构kmergent StrUtUre）（生物学 术语，如两栖类动物进行化为鸟类人这一突变结构并不是隐喻所涉及的二个源结 构与靶结构的简单相加＊ut and paste combinaion人而是有独特的内容，有质的 变化，在整和空间中产生新的语义（meedng efUpion），也就是它们的隐喻意义。 内在主义意义观认为意义是演绎逻辑Neductive log峋或形式逻辑（forma logic》而认知语言学认为我们是神经存在（We are neural beings），我们的身体体验 （Cmbodpoefit以及大脑的感知运动kensory－motof）系统在我们的概念体系中起决定 作用。语言材料，语言形式触化中 lip）包括心理空间佃q止d Space卜隐喻 投射加咖…毗喇 ptoection卜概念整合（Conceptua inte剜on）在内的一系列建立在 身体体验基础上的认知过程；概念整合等幕后认知机制产生（ive ise to）语言表 达，语言是这一壮观的认知过程的冰山一角帅 of icebefgh在这篇论文中，作者 论述了计算机隐喻幕后存在的概念整合机制。我们透过计算机隐喻这冰山一角， 试图管窥这一认知过程，认识语义建构、语言使用的认知规律。具体地说，本文 所深入探讨的这些隐喻是概念整合的结果，概念整合支承着（neie）这些隐喻。 而且隐喻并不是人们象掷骰子似（Cfa shOOt）地随意创造出来的，他们是贴切的 （gp人恰当的（聊ropriate人而决定贴切、恰当的因素就是概念整合这一幕后认 知（back卿e co例tion）。更多还原

【Abstract】 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.更多还原