A Cognitive Study Of English Noun-Noun Combination From The Perspective Of Conceptual Integration Theory

Noun-Noun (N-N) combination not only reflects clarity in form and expression, but also exhibits the complicated&profound semantic relationship and associative&connotative meaning. It is the crystallization of language and has been applied to almost every aspects of people’s daily life. It reflects changes in dynamic language and shows the compositionality of language in the raw, serves to expand language and increase language productivity. Applying N-N combination properly can not only make discourse more vivid and beautiful but also promote people to exchange different thought. Therefore, it is of great significance to research on N-N combination. The key viewpoint of this thesis is that N-N combination’s semantic totality is frequently not accumulation of its forming parts but outgrows them.The meaning construction process and understanding mechanism of English N-N combination researches in the past are rarely touched upon or not fully shown. Owing to this and inspired by the mighty explanatory power of Conceptual Integration Theory(CIT) in N-N combination, the author attempts to view the on-line meaning construction of N-N combination as a psychological process of decompression, interaction among elements, then explore their relationships and mappings in detail. By carefully screening, categorizing, analyzing and making a qualitative analysis of the collected data, their backstage understanding mechanism within the theoretical framework of CIT are accounted for, which provides a new perspective to the study of N-N combination. It illustrates why the seemingly illogical N-N combination between two elements does not prevent us from understanding its real meaning.The whole thesis includes the following parts:Chapter1is the introduction including the research background, significance, method and the organization of thesis. Chapter2is the literature review, mainly introducing the history research of N-N combination at home and abroad. Chapter3introduces the working mechanism and brief account of CIT. Chapter4is the data analysis, based on CIT the author picks up40N-N combinations to categorize and analyze their meaning construction by five kinds of conceptual integration networks. Chapter5is the conclusion. The author concludes the contents of this thesis, purposes, achievements and some limitations of this research. Through the data analysis, the author mainly gets the following achievements:1) Simplex network is a kind of "frame-to-value" blending sub-network, relational N-N combination is usually with the structure of modifier and head, so the meaning of relational N-N combination can be constructed by simplex network.2) Mirror network, consisting of four mental spaces with the same organizing frame shared by all mental spaces. The elements of conjunctive N-N combination is usually paralleled, so the meaning of this kind of N-N combination can be constructed by mirror network.3) Single-scope network is much more powerful in meaning construction than others especially with construal of metaphor. One element of the property-mapping N-N combination is usually with vivid character modifying the other and it is evident in metaphor comprehension and use, so the meaning of this kind of N-N combination can be constructed by single-scope network.4) Double-scope network is the network with two different organizing frame. The blend of double-scope network is structured by aspects of both input frames. Hybrid N-N combination creates a new concept in which both input spaces project certain properties onto it. So the meaning of hybrid N-N combination can be constructed by double-scope network.5) In multiple blend network, the mental spaces can be used as input spaces again and again. Blended N-N combination creates a new concept in which neither input I nor input II shares, the blend of multiply blend network is constructed by aspects of all other further input frames. So the meaning of blended N-N combination can be constructed by multiple blend networks.This thesis not only broadens the application scope of CIT but also enriches the study of N-N combination. The author hopes this thesis can make a little contribution to promoting English vocabulary teaching and intellectual machine translation. Although the author has made great effort to this study, there are still limitations of subjectivity. Thus, the author expects that more and more thorough and further research will be done in this area in the future.