黄体芳社会交游考察

作为晚清从浙南一隅的瑞安走出并颇具区域乃至全国性影响的官僚士大夫，黄体芳的社会交游十分广泛。他与张之洞、张佩纶、何金寿等清流士大夫基于同年、同事以及朋友、姻亲关系而构建的人际网络，在清流作为一个政治群体崛起于同光之际前，就已基本形成，并因清议活动而具鲜明的政治色彩。而他与孙衣言、袁昶、张謇、王仁堪等江南士人的广泛交游，无论是其以丈会友、广结奥援的交往目的，还是诗文唱酬、游宴小集的交往方式，都更具文人之间人际交往的传统色彩。     

从Google数字图书馆看当前图书馆的局限和革新

从Google数字图书馆、万方数据和版权所有者之间的版权之争入手,结合当前互联网应用的发展趋势,分析了图书馆在发展过程中面临的问题,并对图书资源数字化过程中如何更好地保护作者版权的问题进行了深入的探讨。     

Nowcasting with Google Trends in an Emerging Market

Most economic variables are released with a lag, making it difficult for policy‐makers to make an accurate assessment of current conditions. This paper explores whether observing Internet browsing habits can inform practitioners about aggregate consumer behavior in an emerging market. Using data on Google search queries, we introduce an index of online interest in automobile purchases in Chile and test whether it improves the fit and efficiency of nowcasting models for automobile sales. Despite relatively low rates of Internet usage among the population, we find that models incorporating our Google Trends Automotive Index outperform benchmark specifications in both in‐sample and out‐of‐sample nowcasts, provide substantial gains in information delivery times, and are better at identifying turning points in the sales data. Copyright © 2011 John Wiley & Sons, Ltd.     

Google在专题信息检索中的作用

结合实例介绍了Google Scholar和Google图书搜索等Google特色产品在专题信息检索中的实际应用。     

基于Maplnfo和CorelDraw的校园平面图编制方法研究

本文以安阳师范学院校园平面图的制作为例，介绍了基于Google Eartb辅以GEtScreen和GlobalMapper获取校固的遥感影像底图，利用Maplnfo进行地图要素数字化，并导入CorelDraw进行整饰出图的平面图制作流程。最后讨论了校园图制作过程中的关键技术以度数据精度的控制方法。     

Google群集及其软件技术分析

本文介绍了Google群集体系结构,并在分析Google搜索引擎工作原理的基础上介绍了它所采用的页面等级算法、超文本匹配算法以及利用最新推出的Google API的软件开发技术,为认识及二次开发利用Google提供了全面的资料.     

浅析学术搜索引擎——Google Scholar

Google Scholar学术搜索引擎是一种纯学术性的搜索引擎,具有专业性强、覆盖面广、搜索功能好、使用便捷等特点,是科学研究强有力的参考工具。对Google Scholar的检索功能、使用方法、结果显示及其使用价值进行了简要分析。     

国槐行道树主要虫害发生特点及防治对策

根据大同市国槐行道树病虫害发生的特点,指出保护物种多样性、加强树木栽培管理、合理进行生物防治是防治病虫害的根本途径。     

云计算-未来IT技术应用的趋势

云计算代表了信息时代的未来,越来越成为人们所关注的一个名词。通过阐述云计算的概念,云计算的应用现状,来描绘云计算的未来及面临的挑战和需要解决的问题。     

Forecasting private consumption: survey‐based indicators vs. Google trends

In this study we introduce a new indicator for private consumption based on search query time series provided by Google Trends. The indicator is based on factors extracted from consumption‐related search categories of the Google Trends application Insights for Search. The forecasting performance of the new indicator is assessed relative to the two most common survey‐based indicators: the University of Michigan Consumer Sentiment Index and the Conference Board Consumer Confidence Index. The results show that in almost all conducted in‐sample and out‐of‐sample forecasting experiments the Google indicator outperforms the survey‐based indicators. This suggests that incorporating information from Google Trends may offer significant benefits to forecasters of private consumption. Copyright © 2011 John Wiley & Sons, Ltd.