With the intensifying urbanization and the increasing demands for land resources, urban development is gradually expanding into the underground. Rational development and design of underground space can not only improv...With the intensifying urbanization and the increasing demands for land resources, urban development is gradually expanding into the underground. Rational development and design of underground space can not only improve use efficiency of land, relieve land use pressure, but also facilitate people's living and improve urban environment. Analysis of the status quo and problems of underground space design researches in China, and the directions of future underground space research and development will contribute to the development and design of underground space. On the basis of reviewing research papers in the past decades, the contents of underground space researches were divided into 10 major categories, the current contents of underground space researches in China and existing problems were analyzed, and it was proposed that the future underground space design researches should be based on traditional research contents and methods, use advanced technologies such as information technology, show the interdisciplinary cooperation, pay attention to human feelings, protection and continuation of cultural context, and adhere to green and sustainable development with consistent innovation and progress.展开更多
国内外研究者通常认为,英语动词不定式中的to只是一个标记,只有语法功能,并无词汇意义。这种观点没有弄清to在英语非限定动词系统中的意义,也没有廓清英语介词to与其之间的认知联系。英语介词to的原型意义为动体对界标的空间趋向性,这...国内外研究者通常认为,英语动词不定式中的to只是一个标记,只有语法功能,并无词汇意义。这种观点没有弄清to在英语非限定动词系统中的意义,也没有廓清英语介词to与其之间的认知联系。英语介词to的原型意义为动体对界标的空间趋向性,这种空间趋向性通过隐喻投射表示动体时间对界标时间的趋向性,表示将来时间。通过系统分析英语动词不定式中to的用法、对比英语非限定动词形式to+V、V-ing和V-ed在英语语言中的系统作用可以发现,英语动词不定式中的to既有表示"相对将来时间"的意义,也有无意义的情况。由此可以得出英语to的意义的认知扩展路径:动体对界标的空间趋向性→动体时间对界标时间的趋向性→相对的将来时间→无意义/0,该路径是Hopper&Traugott的"语法化斜坡(cline of grammaticality)"1在英语语言中的一个具体体现。展开更多
为了能够快速有效地将中文商品评论识别为好评或差评,提出一种算法。针对不同类别的商品,预先根据其评论语料构建领域情感词典,评论文本与情感词典集匹配提取情感特征,构建情感特征向量空间模型SF-VSM(Sentiment Feature Vector Space M...为了能够快速有效地将中文商品评论识别为好评或差评,提出一种算法。针对不同类别的商品,预先根据其评论语料构建领域情感词典,评论文本与情感词典集匹配提取情感特征,构建情感特征向量空间模型SF-VSM(Sentiment Feature Vector Space Model),解决传统的特征向量空间模型维数较高及特征选择误差问题。然后基于该模型结合改进的多项式朴素贝叶斯方法对评论进行情感倾向分类。实验结果表明,相比分别基于原始特征和基于χ2特征选取的朴素贝叶斯分类算法,该算法分类精度较高且分类速度快。展开更多
基金Sponsored by Sichuan Provincial Science and Technology Support Program(2015SZ0232)
文摘With the intensifying urbanization and the increasing demands for land resources, urban development is gradually expanding into the underground. Rational development and design of underground space can not only improve use efficiency of land, relieve land use pressure, but also facilitate people's living and improve urban environment. Analysis of the status quo and problems of underground space design researches in China, and the directions of future underground space research and development will contribute to the development and design of underground space. On the basis of reviewing research papers in the past decades, the contents of underground space researches were divided into 10 major categories, the current contents of underground space researches in China and existing problems were analyzed, and it was proposed that the future underground space design researches should be based on traditional research contents and methods, use advanced technologies such as information technology, show the interdisciplinary cooperation, pay attention to human feelings, protection and continuation of cultural context, and adhere to green and sustainable development with consistent innovation and progress.
文摘国内外研究者通常认为,英语动词不定式中的to只是一个标记,只有语法功能,并无词汇意义。这种观点没有弄清to在英语非限定动词系统中的意义,也没有廓清英语介词to与其之间的认知联系。英语介词to的原型意义为动体对界标的空间趋向性,这种空间趋向性通过隐喻投射表示动体时间对界标时间的趋向性,表示将来时间。通过系统分析英语动词不定式中to的用法、对比英语非限定动词形式to+V、V-ing和V-ed在英语语言中的系统作用可以发现,英语动词不定式中的to既有表示"相对将来时间"的意义,也有无意义的情况。由此可以得出英语to的意义的认知扩展路径:动体对界标的空间趋向性→动体时间对界标时间的趋向性→相对的将来时间→无意义/0,该路径是Hopper&Traugott的"语法化斜坡(cline of grammaticality)"1在英语语言中的一个具体体现。
文摘为了能够快速有效地将中文商品评论识别为好评或差评,提出一种算法。针对不同类别的商品,预先根据其评论语料构建领域情感词典,评论文本与情感词典集匹配提取情感特征,构建情感特征向量空间模型SF-VSM(Sentiment Feature Vector Space Model),解决传统的特征向量空间模型维数较高及特征选择误差问题。然后基于该模型结合改进的多项式朴素贝叶斯方法对评论进行情感倾向分类。实验结果表明,相比分别基于原始特征和基于χ2特征选取的朴素贝叶斯分类算法,该算法分类精度较高且分类速度快。
