Starting with the introduction of current development of Business English in China, the paper points out the problems existing in the disciplinary orientation of Business English. On the basis of discussing the decisi...Starting with the introduction of current development of Business English in China, the paper points out the problems existing in the disciplinary orientation of Business English. On the basis of discussing the decisive factors in the disciplinary orientation of Business English, the paper concludes that Business English is an interdisciplinary subject which has practical applications, and Business English should take linguistics and economics as its theoretical basis.展开更多
This paper attempts to explore the functional divergence of LD （Left Dislocation） in English and Chinese. Through detailed analyzing, we find that LD in both languages shares only one function, the function of simpl...This paper attempts to explore the functional divergence of LD （Left Dislocation） in English and Chinese. Through detailed analyzing, we find that LD in both languages shares only one function, the function of simplifying, but it is different in other functions and there are eight more functions in Chinese than in English. The interface study of LD in the two languages leads to the implications： The connections between syntactic form and discourse function are language-specific and arbitrary, and LD serves a wide variety of discourse functions and is motivated by a range of discourse circumstances展开更多
As the popularity of digital images is rapidly increasing on the Internet, research on technologies for semantic image classification has become an important research topic. However, the well-known content-based image...As the popularity of digital images is rapidly increasing on the Internet, research on technologies for semantic image classification has become an important research topic. However, the well-known content-based image classification methods do not overcome the so-called semantic gap problem in which low-level visual features cannot represent the high-level semantic content of images. Image classification using visual and textual information often performs poorly since the extracted textual features are often too limited to accurately represent the images. In this paper, we propose a semantic image classification ap- proach using multi-context analysis. For a given image, we model the relevant textual information as its multi-modal context, and regard the related images connected by hyperlinks as its link context. Two kinds of context analysis models, i.e., cross-modal correlation analysis and link-based correlation model, are used to capture the correlation among different modals of features and the topical dependency among images induced by the link structure. We propose a new collective classification model called relational support vector classifier (RSVC) based on the well-known Support Vector Machines (SVMs) and the link-based cor- relation model. Experiments showed that the proposed approach significantly improved classification accuracy over that of SVM classifiers using visual and/or textual features.展开更多
文摘Starting with the introduction of current development of Business English in China, the paper points out the problems existing in the disciplinary orientation of Business English. On the basis of discussing the decisive factors in the disciplinary orientation of Business English, the paper concludes that Business English is an interdisciplinary subject which has practical applications, and Business English should take linguistics and economics as its theoretical basis.
文摘This paper attempts to explore the functional divergence of LD （Left Dislocation） in English and Chinese. Through detailed analyzing, we find that LD in both languages shares only one function, the function of simplifying, but it is different in other functions and there are eight more functions in Chinese than in English. The interface study of LD in the two languages leads to the implications： The connections between syntactic form and discourse function are language-specific and arbitrary, and LD serves a wide variety of discourse functions and is motivated by a range of discourse circumstances
基金Project supported by the Hi-Tech Research and Development Pro-gram (863) of China (No. 2003AA119010), and China-American Digital Academic Library (CADAL) Project (No. CADAL2004002)
文摘As the popularity of digital images is rapidly increasing on the Internet, research on technologies for semantic image classification has become an important research topic. However, the well-known content-based image classification methods do not overcome the so-called semantic gap problem in which low-level visual features cannot represent the high-level semantic content of images. Image classification using visual and textual information often performs poorly since the extracted textual features are often too limited to accurately represent the images. In this paper, we propose a semantic image classification ap- proach using multi-context analysis. For a given image, we model the relevant textual information as its multi-modal context, and regard the related images connected by hyperlinks as its link context. Two kinds of context analysis models, i.e., cross-modal correlation analysis and link-based correlation model, are used to capture the correlation among different modals of features and the topical dependency among images induced by the link structure. We propose a new collective classification model called relational support vector classifier (RSVC) based on the well-known Support Vector Machines (SVMs) and the link-based cor- relation model. Experiments showed that the proposed approach significantly improved classification accuracy over that of SVM classifiers using visual and/or textual features.
