低维显式语义空间下的语义关联度计算方法

语义关联度计算是数据科学中的一个关键性基础问题,在信息检索及自然语言处理等方面有着广泛的应用.针对ESA (Explicit Semantic Analysis)算法存在的局限性,提出一种显式语义特征选择算法,并构建低维语义空间.在此基础上,根据特征概念在Wikipedia中的映射信息,提出一种低维显式语义空间下的语义关联度计算方法.该方法解决了ESA算法在后续语义关联度计算过程中,因高维稀疏空间导致计算效果不够准确的问题.实验结果表明,与当前其他方法相比,该方法的计算结果在皮尔逊相关系数(P)及斯皮尔曼相关系数(S)上与人们的认知判断之间具有更好的一致性.     

足球比赛场景中交互行为分析方法研究

目前的视频处理研究主要关注足球视频的基础方面的问题, 而在视频语义方面的工作尚不完善。 为此, 对足球比赛视频中存在的交互行为进行分析, 研究了足球比赛视频语义理解的关键问题, 为实现从一般比赛场景去理解和分析比赛进行了有益的探索。 首先进行场景分析, 利用主颜色提取视频中场地区域并标定场地线; 其次, 检测场景中的球员并判定其队属, 同时利用 Kalman 滤波实现对足球目标的跟踪; 最后, 判定球队的进攻方向的目的语义, 同时获取足球真实轨迹, 进行轨迹分割, 识别球员与足球的交互行为, 并在此基础上结合足球领域的知识进行进攻策略的分析。 实验结果表明, 该算法能很好地解决视频分析各阶段的问题, 能有效分析视频中存在的交互行为, 并从足球领域的角度实现进攻策略分析,进攻模式识别结果查准率达到 71% 以上, 查全率达到 85% 以上, 有益于计算机视觉的应用研究和足球视频科学分析。     

Semantic image annotation based on GMM and random walk model

Automatic image annotation has been an active topic of research in computer vision and patternrecognition for decades.A two stage automatic image annotation method based on Gaussian mixturemodel (GMM) and random walk model (abbreviated as GMM-RW) is presented.To start with,GMM fitted by the rival penalized expectation maximization (RPEM) algorithm is employed to estimatethe posterior probabilities of each annotation keyword.Subsequently, a random walk processover the constructed label similarity graph is implemented to further mine the potential correlations ofthe candidate annotations so as to capture the refining results, which plays a crucial role in semanticbased image retrieval.The contributions exhibited in this work are multifold.First, GMM is exploitedto capture the initial semantic annotations, especially the RPEM algorithm is utilized to train themodel that can determine the number of components in GMM automatically.Second, a label similaritygraph is constructed by a weighted linear combination of label similarity and visual similarity ofimages associated with the corresponding labels, which is able to avoid the phenomena of polysemyand synonym efficiently during the image annotation process.Third, the random walk is implementedover the constructed label graph to further refine the candidate set of annotations generated byGMM.Conducted experiments on the standard Corel5k demonstrate that GMM-RW is significantlymore effective than several state-of-the-arts regarding their effectiveness and efficiency in the task of automatic image annotation.     

2D difference gel electrophoresis reference map of a Fusarium graminearum nivalenol producing strain

Fusarium graminearum is widely studied as a model for toxin production among plant pathogenic fungi. A 2D DIGE reference map for the nivalenol‐producing strain 453 was established. Based on a whole protein extract, all reproducible spots were systematically picked and analyzed by MALDI‐TOF/TOF, leading to the identification of 1102 protein species. The obtained map contributes to the annotation of the genome by identifying previously nondescribed hypothetical proteins and will serve as a reference for future studies aiming at deciphering F. graminearum biology and chemotype diversity.     

TargetATPsite: A template‐free method for ATP‐binding sites prediction with residue evolution image sparse representation and classifier ensemble

Understanding the interactions between proteins and ligands is critical for protein function annotations and drug discovery. We report a new sequence‐based template‐free predictor (TargetATPsite) to identify the Adenosine‐5′‐triphosphate (ATP) binding sites with machine‐learning approaches. Two steps are implemented in TargetATPsite: binding residues and pockets predictions, respectively. To predict the binding residues, a novel image sparse representation technique is proposed to encode residue evolution information treated as the input features. An ensemble classifier constructed based on support vector machines (SVM) from multiple random under‐samplings is used as the prediction model, which is effective for dealing with imbalance phenomenon between the positive and negative training samples. Compared with the existing ATP‐specific sequence‐based predictors, TargetATPsite is featured by the second step of possessing the capability of further identifying the binding pockets from the predicted binding residues through a spatial clustering algorithm. Experimental results on three benchmark datasets demonstrate the efficacy of TargetATPsite. © 2013 Wiley Periodicals, Inc.     

Cheminformatics in MS-based environmental exposomics: Current achievements and future directions

Compound annotation using MS/MS data is the major bottleneck in interpretation of mass spectrometry data during non-targeted screening and suspect screening exposomics studies. Apart from compound identification using available databases or mass spectral libraries, the true challenge comes when completely new compounds have to be identified. Along with recent advances in MS instrumentation that set grounds to a new revolutionary age in environmental exposomics, a multitude of cheminformatics annotation approaches has been developed. Herein, we review the basic principles of the cutting-edge cheminformatics MS-based approaches employed in eco-exposome annotation.We give a solid background discussing the eco-exposome concept in relation to the advances in MS instrumentation, and define the three crucial cheminformatics tasks used in the eco-exposome annotation: molecular formula assignment, compound prioritization and compound annotation. The basic principles of compound annotation are discussed, which are based on three approaches of utilizing structural information inherent to MS data. These involve direct, indirect and joint annotation approaches. We assess their performance through the ability to annotate eco-exposome constituents. We discuss future perspectives and give directions to new annotation strategies and performance evaluation protocols aiming to solve current issues hampering the incorporation of cheminformatics annotation approaches in regular eco-exposome annotation workflows.     

基于限制的OLAM任务语义模型

通过对大量决策分析算法的分析,提出了基于限制(Constraint)的OLAM任务语义模型,该模型从一定的逻辑高度对OLAM进行抽象,利用它可以分析OLAM任务的共性,提取OLAM任务执行时的基本操作,这些基本操作的基础是语义片断。文中给出了语义片断之间关联关系的分析和判断方法,提出了基于限制的、具有方向性的语义关联度定义。语义片断间关系的确定是OLAM任务/事务优化的基础。     

基于语义Web的网络资源整合模式研究

语义网络是目前万维网（WWW）的发展方向,它在计算机和人类理解的语义间建立了联系。语义Web是由多种信息源组成．每个信息源都以某个本体的形式表示。为了实现这些信息源的信息共享,在语义网技术的基础上提出了一个基于语义的异构数据的整合模式,并进行简要的分析．以实现校园网知识资源的智能整合。     

论焦循的《尚书》学研究

以焦循所撰<尚书补疏>为考察对象,分析焦循对<尚书>这部古经意义的新探索.焦循维护伪<孔传>的经典地位,是他确认伪<孔传>蕴含着"二帝三王之道"的真谛,体现了经典的古代意义与传注的现代诠释的统一,具有思想史上的价值.同时,焦循提出<舜典>未亡、<大禹谟>和<皋陶谟>原为一篇的猜想,现据<郭店楚墓竹简>所提供的文本,倒可备为一说,值得重视.     

翻译过程中词语弹性的语义阐释

根据语义学理论的基本原理,探讨了英汉词语的核心、外延和认知意义,提出在翻译过程中必须正确把握词语的弹性,才能达到原文和译文之间的“动态对等”。