关于词汇刻意学习的实证研究

本文通过词汇实验来检测刻意词汇学习和伴随词汇学习哪种学习方式更有效,更持久。实验得出的数据显示: 刻意学习比伴随学习更适合高校非英语专业二年级学生,是他们主要的词汇学习方式,而且更有持久性。     

高住低训中EPO变化规律的研究

血清EPO(erythropoietin，促红细胞生成素)与红细胞的生成有密切关系。为确切了解EPO在高住低训中的变化规律，将14名大学生分为高住低训组和低住低训组，每组7人。高住低训组每天低压低氧(2500m模拟高度)暴露12小时；低住低训组在实验期间不进行低氧暴露。两组每天在常压常氧环境下进行一次3000m跑训练。实验为期4周。结果表明，促红细胞生成素在间断性低氧暴露初期就有升高变化，1天后出现高峰，这一高EPO水平一直维持到低压氧暴露结束。另外，对第2次低氧暴露完当天出低压氧仓即刻与常氧暴露10h后所测EPO结果的比较表明，常氧暴露后EPO呈下降趋势，说明间断性低氧暴露对EPO生成存在着慢性积累的过程。低住低训组的EPO水平一直比较平稳，说明常氧环境对EPO的分泌无明显影响。     

A Bayesian feature selection paradigm for text classification

The automated classification of texts into predefined categories has witnessed a booming interest, due to the increased availability of documents in digital form and the ensuing need to organize them. An important problem for text classification is feature selection, whose goals are to improve classification effectiveness, computational efficiency, or both. Due to categorization unbalancedness and feature sparsity in social text collection, filter methods may work poorly. In this paper, we perform feature selection in the training process, automatically selecting the best feature subset by learning, from a set of preclassified documents, the characteristics of the categories. We propose a generative probabilistic model, describing categories by distributions, handling the feature selection problem by introducing a binary exclusion/inclusion latent vector, which is updated via an efficient Metropolis search. Real-life examples illustrate the effectiveness of the approach.     

空心课文——大学英语教材的批判

空心课文在大学英语教材中所产生的危害,导致课文没有实实在在的内容,没有增加信息和知识。文章提出大学英语教材应该增加扩展非语言知识信息,以解决空心课文的问题。     

播客的社会文本意义解读

本文从符号学和传播学的视角,对国内外迅速兴起的“播客”现象进行较为深入的文本意义解读。笔者认为,作为社会文本的播客,其意义是:在播客特定的语境下,人们借助不同的符号系统,使“自我实现”得到最大的满足并正逐步融入社会。从编码者的角度看,这种“自我的实现”的特点是,话语权力的获得和“超符号”的自由交流。而译码者的“自我实现”的特点,则是通过解释权的回归,使可读的文本和可写的文本得以沟通。     

浅论苏轼“以才学为诗”

宋代诗人喜欢"以才学为诗"。苏轼尤甚。苏轼之所以喜好"以才学为诗",自有其不便言说的独特的创伤初衷,这就是:(1)要抒胸中"忧愁不平气",(2)作家(诗人)与学者兼于一身特殊身份所使然,(3)强烈开宗立派意识所驱使。由此形成了苏轼独特的文本类型,即:(1)用典使事型,(2)多次韵型,(3)艺术鉴赏型,(4)因物寓理型。同时,苏轼在"以才学为诗"的实际操作中,自有其一套与之相适应的审美特征:一是经史百家学问穿插互用;二是以才学寓托诗人心志和寻求精神之"适";三是凭才学拓展诗歌题材。此外,苏轼"以才学为诗"具有极其重要的创作意义。     

解析PKS背诵模式的认知优势——基于思维导图和词块的应用

PKS背诵模式从语言学和认知心理学的角度对背诵重新解析.该模式以词块为关键词作为背诵的基本单位,以图片表达词块帮助学习者形成视觉映像,利用思维导图管理词块,再辅助以视听读结合的输入方式,寓背诵于娱乐,激发学习者的学习动机,提高背诵效率.PKS背诵有着强大的认知优势,词块可以清除理解障碍,思维导图可以促进背诵图式的建构,二者结合拥有强大的助记功能.该模式的应用有利于培养学习者的想象力和自主学习能力.     

高校学报的版式设计与文字编排

通过对高校学报版式设计与文字编排的研究分析,指出了高校学报版式设计的重要性,提出了通过追求文字编排中各元素的变化与统一,强调了版式设计要有独创风格,从而更好地满足读者的视觉享受。     

Applying user analytics to uses and effects of social media in China

ABSTRACT

We introduce what user analytics can do in the first half of the paper and then illustrate how to do user analytics in the second half. In the current context, user analytics refers to a set of diverse communication research methods on uses and effects of social media. User analytics has evolved from TV ratings research to online user research. The history illustrates what data sources, measures, and analyses can be used for what types of research questions under user analytics. We discuss the similarities of and differences between user analytics and other methods of computational communication research (e.g. content mining and online experiments), and compare the strengths and weaknesses of user analytics with traditional quantitative methods (e.g. survey). Finally, we present an application study of Chinese bloggers to demonstrate how to employ user analytics methods to study the production, consumption, and effects of user-generated content.     

Negation recognition in medical narrative reports

Substantial medical data, such as discharge summaries and operative reports are stored in electronic textual form. Databases containing free-text clinical narratives reports often need to be retrieved to find relevant information for clinical and research purposes. The context of negation, a negative finding, is of special importance, since many of the most frequently described findings are such. When searching free-text narratives for patients with a certain medical condition, if negation is not taken into account, many of the documents retrieved will be irrelevant. Hence, negation is a major source of poor precision in medical information retrieval systems. Previous research has shown that negated findings may be difficult to identify if the words implying negations (negation signals) are more than a few words away from them. We present a new pattern learning method for automatic identification of negative context in clinical narratives reports. We compare the new algorithm to previous methods proposed for the same task, and show its advantages: accuracy improvement compared to other machine learning methods, and much faster than manual knowledge engineering techniques with matching accuracy. The new algorithm can be applied also to further context identification and information extraction tasks.