基于幂图的属性约简搜索式算法

粗糙集理论是一种新的处理不精确、不完全与不一致数据的数学工具.属性约简是粗糙集理论的重要研究内容之一,已有的属性约简算法主要是基于代数表示与信息表示的方法.同一问题在不同的知识表示下,其求解难度是不同的.文中从改变属性约简问题的知识表示人手,提出了该问题的一种新的表示方式--幂图;给出了基于幂图的属性约简搜索式算法,把属性约简计算问题转化为在幂图中的搜索问题.理论分析表明新算法是有效的,为属性约简研究提供了一条新的途径.     

基于Rough Set理论的小儿常见病诊断智能超媒体系统

本文主要介绍了用VisualBasic和SQLSever开发的小儿常见病诊断智能超媒体系统以及RoughSet理论在该系统中的应用,包括利用RoughSet理论对该系统中的知识库中的知识进行约简和进行正推理和反推理的方法。RoughSet理论的应用,大大提高了该系统的推理效率。     

具有成本约束和噪声数据信息表的知识约简方法

知识约简是基于粗集理论进行数据挖掘的重要步骤获取最优知识约简是典型的Np-hard问题.在实际应用中,数据属性往往具有成本约束,并且数据本身含有噪声.本文提出了将粗集理论与遗传算法相结合来求解这种信息表的最优知识约简和近似知识约简的方法实验结果表明该方法具有很强的全局搜索能力,在有限的代数内找到信息表的最优约简:最小基约简集、最小成本约简集.当信息表含有噪声数据时,该方法能找出信息表的近似知识约简.     

粗糙集理论中概念与运算的信息表示*

粗糙集理论对知识进行了形式化定义,为知识处理提供了一套严密的分析工具,但在代数表示下,粗糙集理论的本质不易被理解,并且,尚无高效的知识约简算法.该文首先建立了知识与信息之间的关系;然后,在此基础上给出了粗糙集理论中概念与运算的信息表示;最后,证明了知识约简在信息和代数两种不同表示下是等价的.这些结论有助于人们深刻理解粗糙集理论的本质,同时,为寻找高效的知识约简算法奠定了基础.     

一种基于区分度矩阵的属性约简及规则提取算法

在RoughSet理论中属性最小约简及规则提取是NP-hard的。通过研究Rough Set理论中属性约简和值约简问题,提出了区分度矩阵的概念,同时利用矩阵中属性区分度的信息,提出了一种获取属性约简及规则提取的简化算法。实验结果表明,该算法是正确、有效、可行的。     

一种粗糙集属性约简算法

该文针对RoughSet理论的属性约简进行了研究。利用RoughSet和信息论的相关知识,研究了通过可辨识矩阵求得属性约简集,并利用条件熵来计算属性约简集中属性间的相关性,其平均值最小的属性集即为求得的最佳属性约简的结果。实验证明,它可以取得比较理想的效果。最后利用该文的方法给出了对UCI机器学习数据库的例子的约简结果。     

基于粗糙集理论的约简、决策规则与模式

粗糙集理论的概念性框架之一就是利用不可分辨关系和布尔推理作为数据约简和获取决策规则的基础.在分辨矩阵和决策矩阵概念的基础上,提出将约简分为4类,即信息表的对象约简、信息表的全局约简、决策表的对象约简和决策表的全局约简,其中决策表的对象约简对应决策规则.从模式的角度对约简和决策规则进行了分析,利用决策矩阵和决策函数,给出了获取最小决策规则的一种算法,上述结论可以作为设计启发式算法的基础,并用例子对结论进行了说明.     

基于粗糙集的属性约简算法

本文主要研究基于粗糙集理论的属性约简算法.提出了一种同时适合于相容信息表和不相容信息表的启发式约简算法,并通过算例验证了该算法的可行性和有效性.     

基于Rough Set的数据预处理

RoughSet理论是一种新的处理不精确,不完全与不相容知识的数学工具。数据预处理是数据挖掘中必不可少的步骤,处理的结果对下一步数据挖掘有直接影响。论文利用RoughSet一些特性对KDD99中的数据集进行处理,并且针对数据集的特点实现了对其进行数据离散化、属性约简等处理。通过这些处理过程为下一步的数据挖掘打下了基础。     

基于Rough集的信息约简方法

本文主要针对Rough集理论本身以及基于Rough集理论的信息表的约简方法进行研究。并在原有的Rough集理论关于信息表约简方法的基础上提出了一种新的信息表约简的方法-简单相异矩阵法。     

A conceptual theory of part-whole relations and its applications

This paper shows two applications of a theory of part-whole relations that has been introduced in [1] in two different areas: natural language semantics and modelling parts of physical objects. A short overview of the theory will be given, followed by two sections which present results in the two application areas. In Section 2 we provide an analysis of the domain of solid objects like devices, buildings and other artifacts of our daily life. We first examine in more detail the relevant part-whole relations in that domain. The second part describes how these relations can be represented and manipulated in a hybrid system. In Section 3 it will be shown that there is a strong and immediate correspondence between classes of part-whole-relations and syntactically or lexically motivated classes of genitive constructions. The two applications illustrate the generality of the theory as well as its usefulness for representing and reasoning about part-whole information in totally different domains.     

基于网格计算市场模型的资源与作业描述语言的研究

网格计算市场模型是把经济学的概念应用到网格的资源管理和作业调度中的模型。本文分析了网格计算市场模型中资源和作业描述语言的需求,简要介绍了资源和作业描述语言Classified Advertisements(Classad),指出它在网格计算市场模型中描述资源和作业的不足之处,对它做了相应的改进和扩充．以实现在经济模型下对资源和作业更加灵活、细枉度的描述。     

Expressiveness and language choice

Specialized languages are often more appropriate than general languages for expressing certain information. However, specialized languages must be chosen carefully because they do not allow all sets of facts to be stated. This paper considers the problems associated with choosing among specialized languages. Methods are presented for determining that a set of facts is expressible in a language, for identifying when additional facts are stated accidentally, and for choosing among languages that can express a set of facts. This research is being used to build a system that automatically chooses an appropriate graphical language to present a given set of facts.     

NDKAS中知识的理论表示方法及其描述语言的设计

知识的理论表示方法是基于属性描述的概念获取系统中一种有效的知识表示方法，它具有层次性，抽象性、模块性和完整性等特点。本文给出了理论表示方法及其描述语言的定义和应用实例。     

基于卷积神经网络的中文医疗弱监督关系抽取

随着医疗领域受到越来越多的关注,自然语言处理的理论和应用逐渐拓展到该领域,其中信息抽取技术在该领域的应用成为研究热点。针对信息抽取技术在医疗领域实体关系抽取中的应用,提出一种基于卷积神经网络的弱监督关系抽取方法。该方法通过添加人工规则使训练语料带有实体关系标签,然后将该弱关系训练语料转换为向量特征矩阵,并输入到卷积神经网络进行分类模型训练,最终实现实体关系抽取。实验结果表明,该方法比常规机器学习方法更加准确高效。     

面向中间语义表示格式的汉语口语解析方法

口语解析在人机对话系统和口语翻译系统中的作用是十分关键的。本文提出了一种统计和规则相结合的汉语口语解析方法,解析结果是一种中间语义表示格式。该方法分为两个阶段。首先,采用统计方法,解析出输入句子的语义信息,然后,利用规则,将这些语义信息映射到中间语义表示格式。试验证明,此方法具有较强的鲁棒性,而且避免了完全用规则方法解析的一些弊端,达到较高的解析正确率。     

Towards a cognitive foundation for knowledge representation

Abstract. Knowledge engineering, knowledge management and conceptual modelling are concerned with representing knowledge of business and organizational domains. These research areas use ontologies for knowledge representation. Ontologies are understood either in the philosophical sense as firm metaphysical commitments or in the looser sense of dictionaries or taxonomies.
This paper critically examines the understanding and use of ontologies and knowledge representation languages in information systems (IS) research and application. As ontologies are intended to be conceptualizations of a perceived reality, they should reflect the empirically observed reality. This motivates proposing psychology of language as a reference discipline for knowledge engineering and knowledge management. Natural language is argued to reflect the cognitive concepts we use to think about and perceive the world around us. These cognitive concepts are the relevant terms with which to structure and represent knowledge about the world.
Psychology of language can provide empirical justification for a particular set of concepts to represent knowledge. This paper draws on psycho-linguistic research to develop a proposal for a system of cognitive structures. This is argued to provide the relevant concepts on which to found knowledge representation schemata for knowledge engineering, knowledge management and conceptual modelling.     

Efficient Implementation of Semantic Relations in Lexical Databases

In this paper we develop a formalization of semantic relations that facilitates efficient implementations of relations in lexical databases or knowledge representation systems using bases. The formalization of relations is based on a modeling of hierarchical relations in Formal Concept Analysis. Further, relations are analyzed according to Relational Concept Analysis, which allows a representation of semantic relations consisting of relational components and quantificational tags. This representation utilizes mathematical properties of semantic relations. The quantificational tags imply inheritance rules among semantic relations that can be used to check the consistency of relations and to reduce the redundancy in implementations by storing only the basis elements of semantic relations. The research presented in this paper is an example of an application of Relational Concept Analysis to lexical databases and knowledge representation systems (cf. Priss 1996) which is part of a larger framework of research on natural language analysis and formalization.     

Specification,proof, and model checking of the Mondex electronic purse using RAISE

This paper describes how the communication protocol of Mondex electronic purses can be specified and verified against desired security properties. The specification is developed by stepwise refinement using the RAISE formal specification language, RSL, and the proofs are made by translation to PVS and SAL. The work is part of a year-long project contributing to the international grand challenge in verified software engineering. J. C. P. Woodcock