用Excel处理化学中的计算问题

利用Excel处理化学中算术平均值、平均偏差、相对平均偏差、标准偏差、相对标准偏差、物质的量浓度、溶液的H+浓度、溶液的pH值、缓冲溶液等一些常见的数据处理和计算问题。     

一种双向聚类协同过滤推荐算法研究

针对传统协同过滤推荐算法在大数据环境下存在数据稀疏性及计算复杂性等问题,提出一种双向聚类协同过滤推荐算法。该算法首先从用户维度和项目维度两个方向分别进行属性聚类,然后在目标用户和目标项目所在类簇中分别使用改进后的相似度计算方法进行协同过滤推荐,最后通过平衡因子综合预测评分并形成最终推荐列表。在 MovieLens 公开数据集上进行实验,结果表明,该算法（DCF）相比传统协同过滤推荐算法（TCF）、基于用户聚类的协同过滤推荐算法（UCF）以及基于项目聚类的协同过滤推荐算法（ICF）,在平均绝对误差上分别降低了 16%、8.1%、7.5%,有效提高了推荐精度。     

联合分析方法在个人信息隐私研究中的机会分析

[目的/意义]为更全面地了解联合分析方法在个人信息隐私研究中的应用以及发现潜在的研究机会,为信息隐私保护的深入研究提供参考和借鉴,有必要对采用联合分析方法研究个人信息隐私的文献进行回顾总结。[方法/过程]研究个人信息隐私且采用联合分析方法的20篇文献被选出来,重点对这些文献的研究主题、采用的研究理论以及协同使用的其他研究方法进行了总结和分析。[结果/结论]结果发现：第一,现有相关研究主要集中在数据共享意愿和产品采纳两个方面;第二,这些文献很少采用用户隐私披露意向和行为研究中的相关理论来指导属性的选择和结果的解释;第三,联合分析与焦点小组访谈、聚类分析、问卷调查等方法相结合可以提供更多的理论和实践启示。     

A network-based concept extraction for managing customer requests in a social media care context

Web 2.0 changed everyday life in many aspects, including the whole system that orbits around the purchase of products and services. This revolution necessarily involved also companies, because customers became increasingly demanding. The diffusion of social media platforms pushed customers to prefer this channel for quickly obtaining information and feedback about what they want to buy, as well as for asking help after the selling. In this framework, many organisations adopted a new way of providing assistance known as social customer care. A direct link to companies allows customers to obtain real-time solutions. In this paper, we introduce a new strategy for automatically managing the information listed in the requests that customers send to the social media accounts of companies. Our proposal relies on the use of network techniques for extracting high-level structures from texts, highlighting the different concepts expressed into the customers’ written requests. The texts can be then organised on the basis of this new emerging information. An application to the requests sent to the AppleSupport service on Twitter shows the effectiveness of the strategy.     

基于网格的并行数据挖掘算法的实现

随着信息技术的发展,大量的数据不断被收集和存储,对数据的挖掘规模越来越大,传统的数据挖掘已经无法解决海量数据挖掘问题。网格技术的发展,使得广域分布的海量数据的挖掘问题得到解决。文章根据现实中海量数据挖掘的需求和网格的本质,把并行关联规则挖掘算法应用于网格数据挖掘中,并建立了一个并行数据挖掘模型,验证了并行数据挖掘系统在网格环境的可行性与合理性。     

大数据环境下可视媒体版权保护模式研究

大数据技术的快速发展与应用,加快了可视媒体大数据的传播与利用。可视媒体数据的特点与广泛应用也带来了一些新的可视媒体大数据安全性问题。构建网络环境可视媒体大数据版权保护模式,可为数字图书馆可视媒体应用服务提供安全保障,增强图书馆数字资源综合服务能力。充分挖掘可视媒体价值稀疏性与视觉稀疏性,提取可视媒体稀疏特征,建立可视媒体大数据稀疏感知计算模型,从可视媒体稀疏特性角度给出可视媒体大数据版权加密、版权认证、版权告示与版权审计追踪方案设计思路,构建可视媒体大数据版权保护应用新模式。结合数字图书馆应用实践验证了该版权保护模式的有效性,该版权保护模式可较好维护数字图书馆中可视媒体大数据机密性、完整性、可用性、可审计性,切实提升大数据环境数字图书馆可视媒体内容服务能力。     

再谈实验数据处理方法的合理选择

实验误差分析是实验教学中的一个重要内容,学生常因不能准确理解测量误差的相关概念和分析方法,而采用了错误的实验数据处理方法。针对这一问题,通过电子自旋共振实验的测量误差分析,简述了直接测量、间接测量及不确定度传递的应用;利用脉冲核磁共振实验的数据分析,说明了曲线拟合与拟合不确定度的使用适应性。两者的物理实验结果表明,实验数据处理不是简单的纯计算问题,而是必须遵从严格误差分析原理的技术方法。     

Organization of biomedical data for collaborative scientific research: A research information management system

Biomedical researchers often work with massive, detailed and heterogeneous datasets. These datasets raise new challenges of information organization and management for scientific interpretation, as they demand much of the researchers’ time and attention. The current study investigated the nature of the problems that researchers face when dealing with such data. Four major problems identified with existing biomedical scientific information management methods were related to data organization, data sharing, collaboration, and publications. Therefore, there is a compelling need to develop an efficient and user-friendly information management system to handle the biomedical research data. This study evaluated the implementation of an information management system, which was introduced as part of the collaborative research to increase scientific productivity in a research laboratory. Laboratory members seemed to exhibit frustration during the implementation process. However, empirical findings revealed that they gained new knowledge and completed specified tasks while working together with the new system. Hence, researchers are urged to persist and persevere when dealing with any new technology, including an information management system in a research laboratory environment.     

促进技术监测在政府科研管理中的应用——纳米技术监测应用研究

新形势下提高科研管理质量和效率迫在眉睫。本文提出技术监测方法,即将数据挖掘等计算机前沿技术引入科研管理领域,发展科研管理的数据分析基础,促进了科研管理决策科学化,并在纳米技术领域进行了实证分析。文章最后指出在科研管理领域运用技术监测方法的重要意义。     

How to measure research efficiency in higher education? Research grants vs. publication output

An ongoing debate in the literature on the efficiency of higher education institutions concerns the indicator for research output for use in empirical analysis. While several studies have chosen to use the number of publications as this indicator, others rely on the amount of research grants. The present study investigates whether both measures lead to a similar assessment of universities. In addition, the number of publications belonging to the 10% and 1% most frequently cited papers in the corresponding subject category and publication year are evaluated. We show that there is a high correlation of efficiency values between the estimations using these indicators. This correlation is slightly higher when the efficiency values result from a data envelopment analysis than when they are determined with a stochastic frontier analysis. The results of this study provide helpful guidelines for researchers evaluating the efficiency of universities and are valueable for decision-makers in science policy.