关键词： 谷歌公司   云计算   搜索引擎   云课堂   云办公  

摘要： 自谷歌公司2006年8月在搜索引擎大会上提出“云计算”(Cloud Computing)概念以来,“云计算”便开始作为一种新型技术对社会各个领域产生重大影响。十几年来,正是云计算技术的广泛应用与传播给社会增添了愈加显著的“云”色彩,也让人们在不知不觉中步入“云时代”。2019年底新冠肺炎疫情的暴发与蔓延,则以倒逼之势让“云时代”更加深入人心。霎时之间,云拜年、云看灯、云抗疫、云捐赠、云复工、云招聘、云签约、云办公、云课堂、云讲座等一大批“云××”词语开始充斥于社会生活的方方面面。在此意义上可以不夸张地说,我们已经进入了无所不“云”的时代。在这个万物皆可“云”的“云时代”,“云××”词语显然已经成为人们语言生活的重要组成部分,因而全面正确认识“云××”词语则是一个必要之举。

关键词： 福建厦门   搜索引擎   农产品   村干部   基层干部   关键词   直播   临翔区  

摘要： 在搜索引擎上输入关键词"村干部直播带货",就有几百万条相关信息,可见近来干部直播带货的火爆程度。福建厦门某村村干部变身"网红"为本村农产品"代言",吸引163.8万人次观看;云南临翔区10个乡(镇、街道)的负责人走进直播间,帮助农民和贫困户推销农产品,直播2小时累计成交1980单……为给本地农产品找出路,活跃在一线的基层干部、驻村扶贫工作队员等,纷纷走到台前"吆喝"。

关键词： Search engine   Scholar Google   Educational research   Technology acceptance model   Higher education  

摘要： Teaching empirical educational research in higher education involves implementing a very useful web tool for bibliography/scientific literature research, a search engine specifically employed for scientific papers, such as "Google Scholar". The aim of this study is to examine undergraduate students' acceptance of technology, through their intention to adopt and use a specific search engine for research purposes. To accomplish this goal, a questionnaire was administered to 225 students from two Universities in Greece. The study was based on TAM (Technology Acceptance Model), reinforced by four external determinants (perceived self-efficacy, subjective norms, facilitating conditions and technological complexity), that contributed to the indirect prediction of the behavioral intention to use the particular search engine. The results of the survey confirm that the main factors of TAM, perceived ease of use and perceived usefulness are significant determinants of students' behavioral intention to use Google Scholar. Moreover, perceived self-efficacy, subjective norms, facilitating conditions and technological complexity have an indirect significant effect on behavioral intention. All these factors explain almost 60% of students' behavioral intention to use this search engine. The results of this survey could be beneficial to the enrichment of good educational practices for the additional training of teachers, as well as to the improvement of the students' skills in the implementation of this specific research tool. Besides, more stakeholders, such as librarians, or even human resources of big companies that construct and support similar systems, such as search engines, could also benefit from the present research.

关键词： Ranking algorithm   Information aggregation   Asymptotic learning   Popularity ranking   Personalized ranking   Misinformation   Fake news  

摘要： Ranking algorithms are the information gatekeepers of the Internet era. We develop a stylized model to study the interplay between a ranking algorithm and individual clicking behavior. We consider a search engine that uses an algorithm based on popularity and on personalization. The analysis shows the presence of a feedback effect, whereby individuals clicking on websites indirectly provide information about their private signals to successive searchers through the popularity-ranking algorithm. Accordingly, when individuals provide sufficiently positive feedback to the ranking algorithm, popularity-based rankings tend to aggregate information while personalization acts in the opposite direction. Moreover, we find that, under fairly general conditions, popularity-based rankings generate an advantage of the fewer effect: fewer websites reporting a given signal attract relatively more traffic overall. This highlights a novel, ranking-driven channel that can potentially explain the diffusion of misinformation, as websites reporting incorrect information may attract an amplified amount of traffic precisely because they are few. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Suicide   Internet   Content analysis   Replication   United states   Austria  

摘要： Background: In recent years, efforts in suicide prevention in the United States and Europe have been made to change the conversation on suicide to incorporate more preventive aspects. The majority of information-seeking occurs online. Structured analyses assessing qualitative changes in retrieved online material on suicide over time, however, are scarce. We replicated a content analysis of suicide-related websites retrieved with popular search engines in the United States and Austria aiming to assess how suicide-related online portrayals have changed in the past five years. Method: We retrieved 396 websites using the search term suicide, method-related search terms (e.g., how to hang yourself), and help-related search terms (e.g., suicide help) in the United States and 286 websites from Austrian searches. We performed a content analysis based on media recommendations for suicide reporting and compared the findings to 335 websites in the United States and 396 websites in Austria retrieved in 2013 with the same procedure. Results: In both countries, the number of both protective (United States: p < .001, Austria: p < .001) and harmful characteristics (United States: p < .001, Austria: p < .001) increased. The ratio of protective to harmful characteristics improved to 3.3:1 in the United States and to 2.4:1 in Austria. Limitations: No assumptions about the actual impact of the retrieved contents can be assumed. Conclusion: There has been an increase in potentially protective aspects in online portrayals of suicidality, but also an increase in potentially harmful characteristics, which may suggest an increasing polarization of suicide-related contents. Future prevention efforts need to address this potential polarization.

摘要： In the domain of Information Retrieval, researchers or scientists usually require human participants to interact, test and evaluate a novel system, which is usually called user studies. However, researchers usually perform these studies with small sample size, some of them recruited fewer than 20 participants, which casts doubt on the generalizability and reproducibility of these studies. Generalizability means how reliable the results of relatively small sample size in an experimental setting can be generalized to the outcomes of a larger population. Reproducibility means whether the results from two groups with the same amount of sample size are consistent with each other. In order to examine the generalizability and reproducibility of online user studies in interactive information retrieval systems, we conducted an online user study with large sample size. We reproduced a well-recognized lab user study from Kelly et al. (2015) in an online environment. We established a simulation-based methodology for evaluating the generalizability and reproducibility of the results and then provided guidelines regarding the optimal number of participants for search engine user studies.

关键词： 网络数据   数据采集   搜索引擎   信息保存   数据分析   网页内容   关键字   本地文件  

摘要： 随着移动互联网的日益普及和广泛应用,网络上的资讯成为人们获取信息的重要来源。人们通常根据需求使用百度等搜索引擎,输入关键字,检索所需的网页内容。在浏览网络资讯信息的同时,人们还希望能够将这些信息保存下来,选择适当的方法进行数据分析,得出有效结论,为日后相关决策提供可靠依据。那么如何保存网页上的信息呢?通常情况下,大家会选中网页上需要的信息,然后通过"复制"和"粘贴"操作,保存在电脑的本地文件中。

关键词： 信息技术   课堂教学   德育教育  

摘要： 随着现代化教学的不断革新,学生的思想道德对于每一个学科来讲,都逐渐成为了一项重要的教学内容。在信息技术教学中强化德育教育,让学生在信息技术教学中树立正确的世界观、人生观、价值观,充分发挥现代信息技术的积极作用,实现课堂有效性的最大化尤为重要。本文以《搜索引擎的应用》一课为例,探讨在信息技术教学实践中如何渗透德育教育。

关键词： 疑难文献   著录   查证   搜索引擎  

摘要： 通过3篇特殊文献的查找和著录,为参考文献的查找和规范著录提供借鉴.通过文献题名在国内外大型搜索网站上查找文献的原始出处,通过对比推敲确定文献的著录项目.最终找到了3篇复杂疑难文献的出处并进行规范著录.作者和编辑在著录文献时要多些耐心,熟悉利用不同搜索引擎和数据库的优点和特点,发挥工匠精神,认真准确完成参考文献的著录.

关键词： 用户日志分析   搜索引擎   排序算法   优化  

摘要： 为提高搜索引擎相关排序算法的搜索结果相关度低下问题,因此提出基于用户日志分析的搜索引擎相关排序算法优化研究。通过构建搜索引擎排序算法的向量空间检索模型来预估排序算法迭代向量,按照用户关注点的不同进行迭代向量分类集合计算,以便求出用户兴趣向量,进行用户兴趣搜索分类,最后由于受分类影响降低了排序结果相关度较低的网页点击率,因此引入时间反馈因子优化迭代排序计算。经实验证明,基于用户日志分析的搜索引擎相关排序算法有效提高了搜索结果的相关性,因此具有更强的排序能力。