Paper-patent citation linkages as early signs for predicting delayed recognized knowledge: Macro and micro evidence

In this study, we investigate the extent to which patent citations to papers can serve as early signs for predicting delayed recognized knowledge in science using a comparative study with a control group, i.e., instant recognition papers. We identify the two opposite groups of papers by the Bcp measure, a parameter-free index for identifying papers which were recognized with delay. We provide a macro (Science/Nature papers dataset) and micro (a case chosen from the dataset) evidence on paper-patent citation linkages as early signs for predicting delayed recognized knowledge in science. It appears that papers with delayed recognition show a stronger and longer technical impact than instant recognition papers. We provide indication that in the more recent years papers with delayed recognition are awakened more often and earlier by a patent rather than by a scientific paper (also called “prince”). We also found that patent citations seem to play an important role to avoid instant recognition papers to level off or to become a so called “flash in the pan”, i.e., instant recognition. It also appears that the sleeping beauties may firstly encounter negative citations and then patent citations and finally get widely recognized. In contrast to the two focused fields (biology and chemistry) for instant recognition papers, delayed recognition papers are rather evenly distributed in biology, chemistry, psychology, geology, materials science, and physics. We discovered several pairs of “science sleeping”-“technology inducing”, such as “biology-biotechnology/pharmaceuticals”, “chemistry-chemical engineering”, as well as some trans-fields science-technology interactions, such as “psychology - computer technology/control technology/audio-visual technology”, “physics - computer technology”, and “mathematics-computer technology”. We propose in further research to discover the potential ahead of time and transformative research by using citation delay analysis, patent & NPL analysis, and citation context analysis.     

The age of Twitter: Donald J. Trump and the politics of debasement

This essay explores the changing character of public discourse in the Age of Twitter. Adopting the perspective of media ecology, the essay highlights how Twitter privileges discourse that is simple, impulsive, and uncivil. This effect is demonstrated through a case study of Donald J. Trump's Twitter feed. The essay concludes with a brief reflection on the end times: a post-truth, post-news, President Trump, Twitter-world.     

移动图书馆信息接受场景识别研究

[目的/意义]为克服普适计算环境对移动图书馆信息接受情境自身来源的多样性和异构性的感知和计算能力不足,以实现用户信息接受的畅体验。[方法/过程]以情境感知理论为基础,采用Hopfield神经网络算法取代情境本体构建和推理,构建移动图书馆场景识别机理模型。[结果/结论]该模型简化移动图书馆场景化情境配置的复杂度,场景识别的正确率可达73%。     

组织专家的检索系统设计与实现

组织专家的检索是当前垂直信息检索研究的热门领域,也是组织信息检索研究的重要内容。本文总结了目前国内外组织专家的检索研究现状,分析了构建组织专家的检索系统的需求和挑战,采用基于相关文档集的归并排序法,利用组织内外的网页和期刊数据库等信息智能识别专家的专长,并基于此设计了从数据资源采集、规整、索引、检索到可视化等整个过程的组织专家的检索系统模型及以武汉大学为例的检索系统平台。     

自助借还书系统中的多书侦测研究

对所借图书进行多书侦测研究,可尽量减少自助式借还书过程中的违规操作,设计一种工作于可见光波段的多书侦测系统。该系统利用摄像装置跟踪被借还图书,提取并分析图书侧面图以判断是否存在违规操作。系统能够自适应地进行图书侧面的识别和提取,具有良好的侦测借还书过程中违规行为的能力。     

Web表格信息抽取研究综述

介绍Web表格的特点与结构、Web表格信息抽取及其过程,分析Web表格信息抽取的4个关键技术：Web表格定位、Web表格结构识别、Web表格内容整合和抽取结果表示,以及Web表格信息抽取的应用。最后指出目前国内外该项研究的不足之处及未来发展方向。     

基于隐马尔科夫模型的中文术语识别研究

基于对中文文本信息语法构成尤其是词性搭配的概率特征的分析,提出一种基于双层隐马尔科夫模型的中文泛术语识别和提取的思路和系统框架,并实现相关系统,基于训练语料对多个领域的文本信息进行术语提取测试。实验结果表明,所提出的基于隐马尔科夫模型的中文泛术语识别和提取思想具有较好的实践参考意义。     

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��[Purpose/significance] This paper proposes the identification of the core research topics and their evolution path visualization methods, in order to provide reference for the field subject evolution analysis research, which has certain significance for revealing the evolution characteristics and development laws of the core topics.[Method/process] Using the LDA model for topic recognition and combining multi-dimensional scaling analysis and visualization techniques to map LDA topic recognition results to two-dimensional space. The topic similarity algorithm was used to detect the association between adjacent time topics, a new visual display method was proposed. We constructed cross-evolution paths of different types of research topics to reveal the dynamic changes of core topics and secondary topics in the evolution process.[Result/conclusion] Taking the medical health information field in China as an example, the research results show that the core research topics in the field of medical and health information in China mainly include electronic health records and Internet medical treatment. Among them, core themes such as health management and smart medical treatment show a good development trend.     

计算机识别汉语同义词的两种算法比较和测评

以词素为单位进行相似度计算 ,在许多方面解决了字面相似度算法中不合理的问题 ,但汉语分词、词义分解、词素分类体系及其编码问题又亟待解决。基于语义的词素相似度算法优于基于单汉字的字面相似度算法 ,是今后的研究重点。表 4。参考文献 9。     

语音信息的内容分析技术研究综述

研究语音信息内容分析的特点，对比文本信息分析处理的异同，对语音信息的内容分析技术进行综述并给出内容分析技术的体系框架,并对语音识别、情感信息的识别、语音识别分类等重难点技术进行研究。