基于主题发现的专利发明人推荐方法

LDA 主题模型可用于识别大规模文档集中潜藏的主题信息,本文提出了一种基于LDA 建立发明人兴趣主题模型的方法,合并每位发明人的专利数据,专利信息基于发明人进行划分,将标准的文档- 主题-词的三层LDA 模型变为专利数据中的发明人- 主题- 词的发明人兴趣模型,实现发明人的主题发现,并利用该模型中主题分布之间的相似性进行发明人的个性化推荐。在采集真实专利数据集上的实验结果表明该方法相比传统的向量空间模型方法和隐马尔科夫模型方法具有更高的准确率,推荐效果更优。     

虚拟学习社区中的人际交互机制研究——以国家级精品课程《现代远程教育》为例

为了研究人际交互机制如何作用于虚拟学习社区,以国家级精品课程《现代远程教育》为例,从横向(学习讨论区—普通讨论区)和纵向(讨论成员、讨论话题、讨论的交互过程)这两个维度来展开讨论并分析案例。     

基于主题地图的异构知识集成*

大型企业和科研机构所处理的信息通常是分布式的，这些信息除了分散在不同的数据库中之外，还以类型各异的文档形式独立存在。为了抽取信息资源中隐含的知识，需要探索数据库及存档文件，把其中有用的知识单元一一挑选出来。为了从整体上对抽取的知识加以把握，还需要把这些知识片段有机地整合起来。本文提出基于主题地图的知识集成系统TMKIS，将信息资源的本体表示规范、存储方式、自动抽取方式、合法性验证以及浏览方式有机地结合起来，利用主题地图技术，处理异构的信息资源，实现异构知识集成的目标。     

叶广芩近期创作的生态意识

叶广芩近期发表的《老虎大福》等一系列动物题材小说，其切入生活视角和审美范式皆不同于其享族系列小说，她把环境保护理念和生态伦理毒祝渗入到小说文本中。其用意在于唤醒人们关注地球生态环境。     

基于主题图的旅游文献组织方法研究*

课题选取四川省阿坝州旅游文献信息资源作为研究个案,按照主题图（Topic Maps）的标准,分析旅游文献组织过程中主题及类型选取原则,定义旅游文献各种主题类型之间的关联关系,结合主题图工具软件提出旅游文献主题图构建方法,并展示旅游文献主题图的组织效果。     

科技期刊提升选题策划质量的途径及实践

【目的】 提升科技期刊选题策划的质量和创新性。【方法】 通过总结《煤炭科学技术》40年来70余次专题策划案例经验,提出选题策划应从类型策划、内容策划、引读语及版面设计进行系统策划。选题内容的策划可以从会议主题、问卷调研及专家咨询获取的最新科技资讯、网络查询行业科技和政策信息、自然来稿、同行及跨行期刊创新选题借鉴、优秀团队科研方向、行业单位策划活动、中国知网等数据库进行精准选题。【结果】 通过上述选题方案的实施,《煤炭科学技术》策划的专题论文被引频次、网络下载率比同期论文高。【结论】 通过系列选题策划方案的实施,可大幅提升科技期刊选题策划的质量和效率。     

Gender diversity in the management field: Does it matter for research outcomes?

This study examines the relationship between gender diversity and research outcomes. Existing research on the topic primarily focuses on how team gender diversity influences scholarly productivity in terms of citations and publication rates. Far less attention has been devoted to the question of how the intellectual contents of research disciplines change as they become more gender diverse. Drawing on a global sample of more than 25,000 management papers, we use natural language processing techniques, correspondence analysis and regression models to illuminate impact-, content- and status-related dimensions of gender diversity in management research. In regression models adjusting for geographical setting, institutional prestige and collaboration patterns, we find no discernable effects of team gender diversity on per-paper scientific impact. In contrast, our analyses converge to yield a broadly consistent pattern of gender-related variations in research focus: women are well-represented in social- and human-centered areas of management, while men comprise the vast majority in areas addressing more technical and operational aspects. Our findings corroborate recent sociological research suggesting that cultural norms and expectations are channeling women and men towards different areas of work and study. We argue that the broadened repertoire of perspectives, values and questions resulting from gender diversity may render management research more responsive to the full gamut of societal needs and expectations.     

Liberation of public data: Exploring central themes in open government data and freedom of information research

This paper conducts a comparative literature survey of Open Government Data (OGD) and Freedom of Information (FOI), with a view to tracking the central themes in the two civil society campaigns. With seeming similarities and a growing popularity in research, the major themes framing research on the two movements have not clearly emerged. Topic modelling, text mining and document analysis methods are used to extract the themes as well as key named entities. The topics are subsequently labeled and with expert guidance, their semantic meaning are provided. The results indicate that the major theme in FOI research borders on issues relating to disclosure, publishing, access and cost of requests. On the other hand, themes in OGD research have largely centered on technology and related concepts. The approach also helped in determining key similarities and differences in the two campaigns as reported in research.     

数据库技术在专题学习网站中的应用

随着网络的发展和广泛应用，Internet中的信息已经由静态方式发展为动态的交互方式，网站与数据库的连接也显得越来越重要。先简要介绍了目前流行的几种Web数据库访问技术，进而详细探讨了数据库技术在专题学习网站中的应用。     

Open data visualizations and analytics as tools for policy-making

Government agencies collect large amounts of structured and unstructured data. Although these data can be used to improve services as well as policy processes, it is not always clear how to analyze the data and how to glean insights for policy making, especially when the data includes large volumes of unstructured text data. This article reports opinions found in “We the People” petition data using topic modeling and visual analytics. It provides an assessment of the usability of the visual analytics results for policy making based on interviews with data professionals and policy makers. We found that visual analytics have potentially positive impacts on policy making practices. Experts also articulated potential barriers regarding the adoption of visual analytics tools, and made suggestions. Potential barriers included insufficient resources in government agencies and difficulty integrating analytics with current work practices. The main suggestions involved providing training and interpretation guidelines along with the visual analytics tools. Major contributions of this study include: (1) suggesting viable visualization tools for analyzing textual data for policy making, and (2) suggesting how to lower barriers to adoption by increasing usability.