共查询到19条相似文献，搜索用时 93 毫秒
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Big6与当代大学生的信息素养构建 总被引：8，自引：0，他引：8
作为世界上最知名的信息问题解决模式，Big6为构建大学生的信息素养提供了科学高效的方法和途径。当前我国高校应积极推广Big6，深化文检课教学改革，探索基于课程整合的信息素养教育。 相似文献
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提高中学生信息素养是一个系统工程,Big6信息问题解决模式强调了学生的主体地位和实际解决问题的能力,充分体现了对学生信息素养的培养。 相似文献
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通过对我国台湾地区中小学图书馆应用Big6将信息素养教育融入教学的研究,建议内地中小学图书馆员与教师合作,应用Big6进行教学,以多媒体的形式呈现教学资源,提高学生的学习兴趣,培养学生的信息素养,逐渐建立起自主学习的意识,最终学会用Big6处理学习和生活中的各种信息问题。 相似文献
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随着社会信息化发展争信息社会的来临，信息越来越成为重要的资源。求职信息是劳动力市场实现就业的基础性资源。在求职过程中，进城农民深感信息短缺，求职不易，这主要缘于信息不平等问题。由于教育分化导致的信息获取能力的差异性、制度阻隔带来的信息接触机会的不均等性以及信息桥缺失引起的信息获取方式的滞后性，进城农民处于信息不平等地位，难以获得和占有信息，是导致其求职难的深层原因。解决进城农民求职难问题，必须坚持社会公正原则，对进城农民信息不平等问题进行有效调适。 相似文献
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现代教育理论认为:教学过程不仅仅是知识信息传递加工的过程,也是情感信息交流、感染的过程,是师生双方在认知和情感两方面同时进行交互作用的过程。但长期以来,在教学的实践活动中,存在着重知轻情的教学失衡状况,对教学活动的矛盾揭示仅显现了矛盾的认识性方面,而忽视了矛盾的情感性方面。这一重大缺陷不仅会影响人们对教学基本问题的更全面、更深入的认识,也会阻碍人们从根本上解决在教育活动中出现的带有普遍性的实际问题,并最终会对教学活动的发展产生消极影响。 相似文献
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【目的/意义】个性化推荐方法是目前解决信息多样化与用户需求专一化之间矛盾的比较有代表性的解决 方案之一。基于内容的推荐系统由于算法本身的局限性和项目特征提取的困难性使得推荐结果过于专门化,不能 给用户提供新颖的推荐项目,本文尝试找到一种兴趣偏好扩散的方法改善推荐专门化的问题。【方法/过程】本文提 出了一种在领域本体中基于信息层次距离和信息损失距离的综合推荐方法,该方法通过基于信息层次距离的相似 性和基于信息损失距离的相似性算法来综合计算项目之间的相似度。【结果/结论】研究表明：领域本体中信息损失 距离对推荐结果能产生较大影响,基于信息层次距离和信息损失距离的综合推荐方法能有效提高推荐结果的多样 性和有用性。 相似文献
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论我国数字图书馆版权问题 总被引：1，自引：0，他引：1
就当前数字图书馆资源建设和信息服务过程中遇到的版权问题进行了探讨,介绍了国外在解决这一问题上所作的努力,并在此基础上对如何逐步解决我国数字图书馆的版权问题提出了若干建议。 相似文献
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《国家科学评论(英文版)》2014,(2)
Big Data bring new opportunities to modern society and challenges to data scientists. On the one hand,Big Data hold great promises for discovering subtle population paterns and heterogeneities that are not possible with small-scale data. On the other hand, the massive sample size and high dimensionality of Big Data introduce unique computational and statistical challenges, including scalability and storage botleneck, noise accumulation, spurious correlation, incidental endogeneity and measurement errors.hese challenges are distinguished and require new computational and statistical paradigm. his paper gives overviews on the salient features of Big Data and how these features impact on paradigm change on statistical and computational methods as well as computing architectures. We also provide various new perspectives on the Big Data analysis and computation. In particular, we emphasize on the viability of the sparsest solution in high-conidence set and point out that exogenous assumptions in most statistical methods for Big Data cannot be validated due to incidental endogeneity. hey can lead to wrong statistical inferences and consequently wrong scientiic conclusions. 相似文献
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大数据挖掘为经济和社会问题研究提供了崭新方法,但对隐私权在内的个人基本权利的潜在侵犯风险不容忽视。归纳大数据挖掘所面临的隐私风险问题,探讨隐私保护数据分析的流程及策略,从数据格式、知识产权、服务条款、社交网络等方面指出网络环境下隐私保护的技术趋势,并就立法完善提出建议。 相似文献
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大数据浪潮在全球范围内呈愈演愈烈的趋势。既有的隐私乱象在灵活多变的大数据影响下,会受到更多的挑战,但同时,大数据也为个人隐私的妥善处理与保护带来了多种可能,危机与机遇并存。全文从新的视角出发,运用哲学的思维,采取以定性论述为主,定量建模为辅的方法,重新探讨信息的时效性,并针对现有的隐私问题逐一进行探究,并分别提出相应的对策。隐私问题不仅关乎个人,更关乎国家,良好的隐私意识和智慧保护技术都将保证现有的隐私问题最终得以妥善解决。 相似文献
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Pasquale Del Vecchio Gioconda Mele Valentina Ndou Giustina Secundo 《Information processing & management》2018,54(5):847-860
This paper aims to demonstrate how the huge amount of Social Big Data available from tourists can nurture the value creation process for a Smart Tourism Destination. Applying a multiple-case study analysis, the paper explores a set of regional tourist experiences related to a Southern European region and destination, to derive patterns and opportunities of value creation generated by Big Data in tourism. Findings present and discuss evidence in terms of improving decision-making, creating marketing strategies with more personalized offerings, transparency and trust in dialogue with customers and stakeholders, and emergence of new business models. Finally, implications are presented for researchers and practitioners interested in the managerial exploitation of Big Data in the context of information-intensive industries and mainly in Tourism. 相似文献
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大数据在地球科学各个学科中的应用越来越受到关注,数据驱动地球科学发现的案例不断出现,有关地球数据信息中心、地球大数据平台及相关学术会议数量逐渐增加,地球大数据正在科学研究上表现出巨大的潜力。科学家对地球大数据的科学方法和工具的需求很大,然而目前地球大数据的理论基础、储存管理和分析方法等仍处于发展之中,对地球大数据的研究和讨论有限。文章通过文献计量学的方法,对科学引文索引(SCI)和社会科学引文索引(SSCI)收录的地球大数据相关文献进行分析,从全球论文的产出数量、国家与机构领域研究影响力、研究主题分布、研究热点变迁和国际合作等多角度,分析揭示了地球大数据研究现状;最后,建议未来重点加强跨学科的地球大数据共享与融合,完善地球科学大数据深度挖掘理论和方法,实现对复杂地球系统的分析、建模与预测,支持和服务全球变化与可持续发展。 相似文献
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保障粮食安全是全球可持续发展的基础及重要议题。粮食可持续生产作为实现粮食安全的基础,同时是应对气候变化、土地退化、生态退化等全球挑战的有效手段。当前,对粮食生产可持续性的监测与评估存在着数据鸿沟,而地球大数据的支撑作用日益凸显。文章总结了地球大数据支撑粮食可持续生产研究的当前实践,包括对地观测技术在粮食生产系统各要素监测中发挥的作用,以及多源数据融合在粮食生产系统综合监测及粮食生产可持续性评估中的应用。在上述实践归纳的基础上,依循实现联合国可持续发展目标(SDGs)的四大杠杆框架,提出了地球大数据支撑粮食可持续生产的2个未来发展方向:多学科模型凝聚地球大数据推动知识发现支撑政府治理;技术创新集成地球大数据搭建产农户智慧生产决策体系。 相似文献
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Over recent years, organizations have started to capitalize on the significant use of Big Data and emerging technologies to analyze, and gain valuable insights linked to, decision-making processes. The process of Competitive Intelligence (CI) includes monitoring competitors with a view to delivering both actionable and meaningful intelligence to organizations. In this regard, the capacity to leverage and unleash the potential of big data tools and techniques is one of various significant components of successfully steering CI and ultimately infusing such valuable knowledge into CI strategies. In this paper, the authors aim to examine Big Data applications in CI processes within organizations by exploring how organizations deal with Big Data analytics, and this study provides a context for developing Big Data frameworks and process models for CI in organizations. Overall, research findings have indicated a preference for a rather centralized informal process as opposed to a clear formal structure for CI; the use of basic tools for queries, as opposed to reliance on dedicated methods such as advanced machine learning; and the existence of multiple challenges that companies currently face regarding the use of big data analytics in building organizational CI. 相似文献
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Big Data Analytics (BDA) is increasingly becoming a trending practice that generates an enormous amount of data and provides a new opportunity that is helpful in relevant decision-making. The developments in Big Data Analytics provide a new paradigm and solutions for big data sources, storage, and advanced analytics. The BDA provide a nuanced view of big data development, and insights on how it can truly create value for firm and customer. This article presents a comprehensive, well-informed examination, and realistic analysis of deploying big data analytics successfully in companies. It provides an overview of the architecture of BDA including six components, namely: (i) data generation, (ii) data acquisition, (iii) data storage, (iv) advanced data analytics, (v) data visualization, and (vi) decision-making for value-creation. In this paper, seven V's characteristics of BDA namely Volume, Velocity, Variety, Valence, Veracity, Variability, and Value are explored. The various big data analytics tools, techniques and technologies have been described. Furthermore, it presents a methodical analysis for the usage of Big Data Analytics in various applications such as agriculture, healthcare, cyber security, and smart city. This paper also highlights the previous research, challenges, current status, and future directions of big data analytics for various application platforms. This overview highlights three issues, namely (i) concepts, characteristics and processing paradigms of Big Data Analytics; (ii) the state-of-the-art framework for decision-making in BDA for companies to insight value-creation; and (iii) the current challenges of Big Data Analytics as well as possible future directions. 相似文献