基于最大公约子范畴的应急决策知识匹配研究

在范畴化知识结构的基础上,提出一种基于最大公约子范畴的知识匹配方法,其解决的主要问题就是通过对决策者的需求和背景知识的匹配,有效量化决策知识的语义处理,提高决策背景知识的萃取效率.实验结果表明,该方法能够同时提高知识匹配过程中的精度和召回率.     

A framework for the verification of infinite-state graph transformation systems

We propose a technique for the analysis of infinite-state graph transformation systems, based on the construction of finite structures approximating their behaviour. Following a classical approach, one can construct a chain of finite under-approximations (k-truncations) of the Winskel style unfolding of a graph grammar. More interestingly, also a chain of finite over-approximations (k-coverings) of the unfolding can be constructed. The fact that k-truncations and k-coverings approximate the unfolding with arbitrary accuracy is formalised by showing that both chains converge (in a categorical sense) to the full unfolding. We discuss how the finite over- and under-approximations can be used to check properties of systems modelled by graph transformation systems, illustrating this with some small examples. We also describe the Augur tool, which provides a partial implementation of the proposed constructions, and has been used for the verification of larger case studies.     

层次分类方法综述

层次分类方法利用类别层次结构来分解问题和组织分类器,可有效解决多类分类问题。依据是否要求类别之间存在显式层次关系,层次分类方法可分为两大类。文中对不要求类别之间存在显式层次关系的层次分类方法进行综述。首先归纳和阐述此类方法所采用的基本框架,然后介绍和分析其中若干关键技术的研究进展,最后从算法和应用两个角度对国内外相关研究进行详细叙述,进而对现有方法进行总结,并给出进一步研究的方向。     

基于范畴论的形式化本体研究

本体技术是语义Web的核心。现有的本体方法都是基于集合论的,本文从范畴论的层次分析了集合论数学的局限性,以及这种局限性对现有本体方法的影响,并探讨基于范畴论的本体方法,通过实例系统说明了范畴论本体的构建方法,并指出范畴论本体所克服的现有本体的不足。     

计算机英语中后置定语的翻译

计算机科学技术的迅猛发展和计算机应用的广泛普及,带动了计算机英语翻译的不断升温。后置定语的广泛运用是计算机英语的一个突出特征。后置定语种类繁多、翻译灵活,是理解计算机英语的一大难关。本文试图通过实例对后置定语的各种翻译方法做逐一地探讨。     

短视频实时判定系统

直播电视产品已经广泛的走入了人们的日常生活中,如CNTV现已拥有央视直播、卫视直播、城市直播、数字直播,共140余路高清直播,并在不断增加,逐步覆盖全国各省、市、地方全部直播频道.直播电视主要由不同种类的电视节目构成,如新闻资讯类、电视谈话类、文艺类、娱乐类、记录片类等等.对于不同种类的电视节目,能够运用计算机进行高效率的实时判定类别将是一项非常有科研意义和实际应用价值的工作.短视频实时判定系统以直播电视节目作为切入点,对其中的广告片段判定做了比较深入和细致的研究,用基于学习的视频类别判定技术和切合实际的程序架构,来实时的分析和标注直播电视节目中的广告片段,并实现了从视频采集到结果展示的完整系统,省去了人工标注视频资料的耗费,使视频分类算法转化成了生产力.     

应用于人脸识别的改进局部保持投影算法

局部保持投影算法（locality preserving projections,LPP）作为降维算法,在机器学习和模式识别中有着广泛应用。在识别分类中,为了更好的利用类别信息,在保持样本点的局部特征外,有效地从高维数据中提取出低维的人脸图像信息并提高人脸图像的识别率和识别速度,使分类达到一定优化,基于LPP算法结合流形学习思想,通过构造一种吸引向量的方法提出一种改进的局部保持投影算法（reformation locality preserve projections ,RLPP）。将数据集利用极端学习机分类器进行分类后,在标准人脸数据库上的进行试验,实验结果证明,改进后算法的识别率优于LPP算法、局部保持平均邻域边际最大化算法和鲁棒线性降维算法,具有较强的泛化能力和较高的识别率。     

程序语言中的共归纳数据类型及其应用

归纳数据类型利用代数方法从构造的角度归纳地描述数据类型的有限语法结构,但在描述动态行为方面存在一定的不足。作为归纳数据类型的范畴对偶概念,共归纳数据类型利用共代数方法从观察的角度共归纳地描述了数据类型的动态行为。首先,从范畴论和代数的角度给出程序语言中的归纳数据类型定义,并分析了相应的递归操作;接着,利用共代数给出共归纳数据类型的范畴论定义,并根据共归纳数据类型的终结性分析了相应的共递归操作;最后,指出如何利用无双代数及分配律将归纳与共归纳数据类型有机地融合起来,探讨数据类型的语法构造与动态行为关系。     

Relevance feedback for category search in music retrieval based on semantic concept learning

Traditional content-based music retrieval systems retrieve a specific music object which is similar to what a user has requested. However, the need exists for the development of category search for the retrieval of a specific category of music objects which share a common semantic concept. The concept of category search in content-based music retrieval is subjective and dynamic. Therefore, this paper investigates a relevance feedback mechanism for category search of polyphonic symbolic music based on semantic concept learning. For the consideration of both global and local properties of music objects, a segment-based music object modeling approach is presented. Furthermore, in order to discover the user semantic concept in terms of discriminative features of discriminative segments, a concept learning mechanism based on data mining techniques is proposed to find the discriminative characteristics between relevant and irrelevant objects. Moreover, three strategies, the Most-Positive, the Most-Informative, and the Hybrid, to return music objects concerning user relevance judgments are investigated. Finally, comparative experiments are conducted to evaluate the effectiveness of the proposed relevance feedback mechanism. Experimental results show that, for a database of 215 polyphonic music objects, 60% average precision can be achieved through the use of the proposed relevance feedback mechanism.