An Advanced Analysis of Cloud Computing Concepts Based on the Computer Science Ontology

Our primary research hypothesis stands on a simple idea:The evolution of top-rated publications on a particular theme depends heavily on the progress and maturity of related topics.And this even when there are no clear relations or some concepts appear to cease to exist and leave place for newer ones starting many years ago.We implemented our model based on Computer Science Ontology(CSO)and analyzed 44 years of publications.Then we derived the most important concepts related to Cloud Computing(CC)from the scientific collection offered by Clarivate Analytics.Our methodology includes data extraction using advanced web crawling techniques,data preparation,statistical data analysis,and graphical representations.We obtained related concepts after aggregating the scores using the Jaccard coefficient and CSO Ontology.Our article reveals the contribution of Cloud Computing topics in research papers in leading scientific journals and the relationships between the field of Cloud Computing and the interdependent subdivisions identified in the broader framework of Computer Science.

叙述文本中中心概念的确定方式及其通达

采用移动窗口技术考察叙述文本中中心概念的确定方式及其通达。实验一在中文条件下得出了与Michelle&O’Brien2002研究一致的结果。实验二采用事件相关方式确定中心词,结果表明,无论在标题相关陪衬词还是在事件相关陪衬词干扰下,事件相关中心词通达效果显著优于边缘词。实验三进一步比较事件相关中心概念与词频相关中心概念的通达效果,结果表明,前者通达效果显著优于后者。总的实验结果表明,事件相关中心的确定方式同样在叙述文本中具有适用性,能够很好地体现文本中心,表现出情境模型水平上的通达优势。

基于中文维基百科的词语语义相关度计算

语义相关度计算在信息检索、词义消歧、自动文摘、拼写校正等自然语言处理中均扮演着重要的角色。该文采用基于维基百科的显性语义分析方法计算汉语词语之间的语义相关度。基于中文维基百科,将词表示为带权重的概念向量,进而将词之间相关度的计算转化为相应的概念向量的比较。进一步,引入页面的先验概率,利用维基百科页面之间的链接信息对概念向量各分量的值进行修正。实验结果表明,使用该方法计算汉语语义相关度,与人工标注标准的斯皮尔曼等级相关系数可以达到0.52,显著改善了相关度计算的结果。

社会媒体短文本内容的语义概念关联和扩展

随着微博、照片分享等社会化媒体的快速发展,每天产生了大量的短文本内容如评论、微博等,对其进行深入挖掘有重大的应用价值和学术意义。该文选取微博作为例子,详细阐述我们提出的方法。微博信息流因其简短和实时的特性而具有非常大的价值,已经成为市场营销,股票预测、舆情监控等应用的重要信息源。尽管如此,微博内容特征极其稀疏、上下文语境提取困难,使得微博信息的挖掘面临着很大挑战。因此,我们提出一种基于Wikipedia的微博语义概念扩展方法,通过自动识别那些与微博信息语义相关的Wikipedia概念来丰富它的内容特征,从而有效提高微博信息数据挖掘和分析的效果。该文工作首先通过可链接性剪枝、概念关联和消歧,发现微博信息中重要的n-gram所对应的Wikipedia概念;其次,采用基于概念-文档关联矩阵的NMF分解(非负矩阵分解)方法获取Wikipedia概念之间的语义近邻,为微博信息扩展相关的语义概念。基于TREC 2011的微博数据集和Wikipedia 2011数据集进行实验,与已有两个相关研究工作比较,该文提出的方法取得了较好的效果。

基于概念的视频检索中概念语义匹配算法研究

为了实现基于概念视频检索中从底层内容到查询的语义贯通,应用基于WordNet词典的语义相似度算法,通过对三种不同原理的算法对比应用,得出基于信息量算法在本应用中更有优势,语义匹配可以提高检索精度,最优映射数目为2至3个,以及在目前发展水平下,映射到合适的概念比检测器精度更合适四个重要结论.

Same or different?Abstract relational concept use in juvenile bamboo sharks and Malawi cichlids

Sorting objects and events into categories and concepts is an important cognitive prerequisite that spares an individual the learning of every object or situation encountered in its daily life.Accordingly,specific items are classified in general groups that allow fast responses to novel situations.The present study assessed whether bamboo sharks Chiloscyllium griseum and Malawi cichlids Pseudotropheus zebra can distinguish sets of stimuli(each stimulus consisting of two abstract,geometric objects)that meet two conceptual preconditions,i.e.,(1)"sameness"versus"difference"and(2)a certain spatial arrangement of both objects.In two alternative forced choice experiments,individuals were first trained to choose two different,vertically arranged objects from two different but horizontally arranged ones.Pair discriminations were followed by extensive transfer test experiments.Transfer tests using stimuli consisting of(a)black and gray circles and(b)squares with novel geometric patterns provided conflicting information with respect to the learnt rule"choose two different,vertically arranged objects",thereby investigating(1)the individuals'ability to transfer previously gained knowledge to novel stimuli and(2)the abstract relational concept(s)or rule(s)applied to categorize these novel objects.Present results suggest that the level of processing and usage of both abstract concepts differed considerably between bamboo sharks and Malawi cichlids.Bamboo sharks seemed to combine both concepts-although not with equal but hierarchical prominence-pointing to advanced cognitive capabilities.Conversely,Malawi cichlids had difficulties in discriminating between symbols and failed to apply the acquired training knowledge on new sets of geometric and,in particular,gray-level transfer stimuli.

基于中文维基百科的领域概念相关性研究

以提高领域概念相关性判断的准确度为研究宗旨,提出综合利用中文维基百科的分类体系结构和概念释义内容进行概念间语义相关度计算的方法。选取中文维基百科分类体系下的图书情报领域的概念为实验对象,将基于分类信息和文本信息的加权算法与单独基于分类信息的语义距离算法和信息量算法,以及基于文本信息的文本重叠算法进行对比分析。实验结果表明:加权算法能取得更好的效果,可为实现面向领域的信息检索、领域本体构建等应用提供重要技术支持。

CONFLICT ANALYSIS APPROACHES FOR INVESTIGATING ATTITUDES AND MISPERCEPTIONS IN THE WAR OF 1812

Formal systems engineering approaches to modeling misperceptions and attitudes are employed within the framework of the graph model for conflict resolution to systematically study the War of 1812 between the United States of America and Great Britain in order to provide enhanced insights into the causes of the war. More specifically, relational definitions for preferences, movements and stability concepts are defined for describing the attitudes and associated behavior of decision makers involved in a conflict. To capture misperceptions of decision makers in the War of 1812, attitudes are studied within the structure of a hypergame. Combining attitudes and misperceptions within the paradigm of the graph model furnishes the flexible analytical tool which demonstrates that misunderstanding of attitudes by Great Britain and the United States may have contributed to the outbreak of this nasty war.

不同知识引出方法对科学概念结构表征的影响——来自多维标度法的证据

不同知识引出方式对获得的群体概念结构的影响,是概念结构研究中重要且未解决的问题。以17名中学化学教师为被试,通过自由分类、概念构图和语义相关性评定,引出被试对15个与原子相关概念的认识,并以多维标度法分析群体概念结构。研究发现:由不同知识引出方式获得的群体概念结构具有不同的特点,通过语义相关性评定获得的群体概念结构更适合呈现科学概念具有复杂关系的特点。研究结果有助于研究者选择合适的研究方法,实施更有效的群体概念结构研究。