基于概念格的概念相似度计算

为了提高信息检索的查全率和查准率,经常要处理相似的概念,因此计算概念间的相似度是必要的.概念由对象和属性两部分组成,所以基于概念格相似度计算的也分为两部分:一是利用概念格的层次关系计算对象的相似度,另一部分计算属性的相似度.其次,概念间的相似度与概念在概念格中的深度有关,计算时利用深度对结果加以修正.计算模型利用了概念较为完整的信息,计算结果与人工判断基本吻合.     

一种基于概念可辨识矩阵的概念约简方法

基于布尔因子分析的概念约简能够保持形式背景的二元关系不变。借鉴概念格中基于可辨识矩阵求解属性约简的思想,在形式背景上定义概念可辨识矩阵,基于此给出保持二元关系不变的概念约简方法。首先,在形式背景上定义一种新的可辨识矩阵,称之为概念可辨识矩阵。该矩阵的行和列都是形式概念,矩阵的每个元素是由属于所在行的形式概念的所有对象和属性对,但不属于所在列的形式概念的对象和属性对构成的集合。其次,研究概念可辨识矩阵与概念协调集之间的关系,利用概念可辨识矩阵给出概念协调集的判定方法。然后,利用概念可辨识矩阵详细讨论核心概念、相对必要概念和不必要概念的特征,进而分别给出判断这3类形式概念的方法。最后,给出基于概念可辨识矩阵寻找概念约简的步骤。     

语义Web的实现：概念标记与概念系统

语义Web是对Web的扩展.Web是被格式标记的信息的集合,语义Web则是被概念标记的信息的集合,扩展的两项措施为信息采用概念标记和计算机内置概念系统.语义由直接语义和引中语义构成,前者为人脑中的观念,后者与语境有关.鏊于目前计算机的能力尚不能模拟语境,不得不"搁置引申语义"和"以概念近似观念",于是就有"语义=概念".概念标记与概念系统是实现语义Web的两大支撑.概念标记就是用概念标记符对将要交由计算机处理的信息进行标记,其面临的主要难点有信息的切分、概念标记符的选用和标记过程的自动化.概念系统就是Ontology,其主要功用是读出信息的直接语义并进行概念推理,后者才是语义Web的最突出特征.概念系统的研究目前主要针对规模庞大、持续性维护、分布式及其集成应用等问题.     

基于最大概念的概念格增量构造算法

针对增量概念格构造过程中,节点更新和生成元判定效率较低、边更新阶段的复杂度较高等问题,提出基于最大概念的概念格增量构造算法,通过跟踪与概念格中的概念具有相同真实内涵的最大概念,简化生成元的判断过程。该算法缩小了寻找新生节点父节点时的搜索范围,避免对生成元非必要边的判断,提高构造概念格的速度。复杂度分析结果表明,该算法的时间性能优于其他同类算法。     

Concept Compression in Formal Concept Analysis Using Entropy-Based Attribute Priority

Discovering important concepts in formal concept analysis (FCA) is an important issue due to huge number of concepts arising out of complicated contexts. To address this issue, this paper proposes a method for concept compression in FCA, involving many-valued decision context, based on information entropy. The precedence order of attributes is obtained by using entropy theory developed by Shannon. The set of concepts is compressed using the precedence order thus determined. An algorithm namely Entropy based concept compression (ECC) is developed for this purpose. Further, similarity measures between the actual and compressed concepts are examined using the deviance analysis and percentage error calculation on the deviance of input weights of concepts. From the experiments, it is found that the compressed concepts inherit association rules to the maximum extent.     

非ISA关系在本体概念相似度计算中的度量方法研究

在本体概念相似度计算过程中,关于本体概念间非ISA关系的处理方法较少。针对本体中存在非ISA概念关系的情况,总结了一些传统的概念相似度计算方法,提出了一种新的适应于非IS八概念关系的相似度计算方法。此方法利用Tversky模型计算本体有向无环概念图的信息量覆盖程度,并结合语义距离方法,再进行权值求和。实验表明,提出的方法可以有效地度量ISA关系,对非ISA关系具有适用性。     

CES 2012展上索尼新概念笔记本

正索尼在CES2012展示了两款概念笔记本——Future Book,这两款外形独特的笔记本分别命名为Hybrid与Slate。Hybrid搭载Windows和Android两大平台的操作系统,其开合模式与传统笔记本大相径庭,采用滑道式开合设计,全尺寸键盘,并配备有手写笔。Hybrid在打开时与普通的笔记本没有太大区别,     

Concept learning games

In this paper, we intend to have a game theoretic study on the concept learning problem in a multi-agent system. Concept learning is a very essential and well-studied domain of machine learning when it is studied under the characteristics of a multi-agent system. The most important reasons are the partiality of the environment perception for any agent and also the communication holdbacks, resulting into a deep need for a collaborative protocol in favor of multi-agent transactions. Here we wish to investigate multi-agent concept learning with the help of its components, thoroughly with a game theoretic taste, esp. on the pre-learning processes. Based on two standard notations, we address the non-unanimity of concepts, classification of objects, voting and communicating protocol, and also the learning itself. In such a game of concept learning, we consider a group of agents, communicating and consulting to upgrade their ontologies based on their conceptualizations of the environment. For this purpose, we investigate the problem in two separate and standard distinctions of game theory study, cooperation and competition. Several solution concepts and innovative ideas from the multi-agent realm are used to produce an approach that contains the reasoning process of the agents in this system. Some experimentations come at the end to show the functionality of our approach. These experimentations come distinctly for both cooperative and competitive views.     

基于属性分类的悲观概念格与乐观概念格

结合实际需求,在给定属性分类的形式背景中,首先定义悲观分类形式背景和乐观分类形式背景及其算子与概念,研究它们与原形式背景的算子、概念之间的关系.然后,对于悲观分类形式背景,建立原概念格与悲观分类概念格之间的映射,给出由原概念格直接生成悲观分类概念格的方法.对于乐观分类形式背景,引入概念包含映射,研究原概念格与乐观分类概念格之间的关系,给出对应的概念格生成方法.最后,通过例子阐述悲观分类概念格与乐观分类概念格在实际问题上的应用及语义解释.     

基于并列结构的概念实例和属性的同步提取方法

在概念实例和属性的提取研究中,针对基于模式的方法召回率比较低的特点,该文提出了一种基于并列结构的概念实例和属性的同步提取方法。首先利用并列结构模式去网页集合中提取同类词语集合,然后再用基于种子的弱指导方法去学习实例和属性共现的上下文模式,最后再通过模式去提取候选实例或候选属性。在此过程中,每提取出一个候选,就将该候选所在的同类词语集合合并到候选集合中。实验结果表明,该文的方法在不降低准确率的基础上,能大大提高提取结果的召回率。     

智慧教学环境下信息化教学设计

随着智慧教学时代的到来,教学模式和教学设计发生了翻天覆地的变化,信息化的教学设计变得至关重要。文章从介绍智慧教学的起源和现状出发,通过对比分析传统教学和智慧教学的差异,借助信息化教学平台,归纳出了智慧教学环境下信息化教学设计完整的设计思路和过程。     

基于负样本精简概念格规则的语义概念检测

为挖掘视频中丰富的语义信息,提出基于负样本精简概念格规则的语义概念检测方法.分析基于概念格的语义分析系统,考虑训练数据中负样本的信息,提出利用负样本精简的语义规则提取算法,将其应用于视频语义检测.先将视频镜头的低层特征映射到低层语义特征,再利用该算法生成语义分类规则,进行视频语义概念检测.实验结果表明,该方法是有效可行...     

基于Web弱指导的本体概念实例及属性的同步提取

该文提出了一种基于Web弱指导的本体概念实例和属性的同步提取方法,利用小规模的种子实例和属性集,该文从Web上自动获取实例和属性共现的上下文模式,并利用种子实例和属性的关联性来评价这些模式。进一步,根据上下文模式提取候选概念实例和属性后,该文提出两种方法来评价提取的候选实例和属性。第一,利用概念实例和属性的关联性来互相评价对方的准确度;第二,利用候选实例或候选属性与种子实例或属性在上下文模式分布上的相似度来评价准确度。在疾病类实验结果表明,人工确认候选实例的准确率在前500个结果达到94%,前1 000个结果的准确率也高达93%。     

ISMS概念模型探索

ISO 27001给出了信息安全管理体系要求方面的最佳实践标准,但并没有说明体系要求方面内在的逻辑关系。该文将ISO 27001分解为过程方法要求和安全控制要求2个部分,在过程方法上按照PDCA的循环模型重新解构了过程方法要求之间的关系,在安全控制上按照主体访问客体的方式重组了安全控制要求之间的关系。     

Concept formation in design

This paper presents a computationally tractable view on where simple design concepts come from by proposing a paradigm for the formation of design concepts based on the emergence of patterns in the representation of designs. It is suggested that these design patterns form the basis of concepts. These design patterns once learned are then added to the repertoire of known patterns so that they do not need to be learned again. This approach uses the notion called the `loosely-wired brain'. This paper elaborates on this idea primarily through implemented examples drawn from the genetic engineering of evolutionary systems, and the qualitative representation of shapes and their multiple representations.     

制造业中的新理念一电子化制造

电子化制造(e-Manufacturing)是一种全新的制造理念,它从电子商务和敏捷供需链的角度将制造工厂和车间与企业管理系统进行集成,从而降低生产成本、提高生产效率。该文介绍了e-Manufacturing的基本概念及其体系结构,论述了e-Manufacturing与数字化制造的区别与联系,分析了适合我国国情的e-Manufacturing实施策略。     

制造业中的新理念——电子化制造

电子化制造(e-Manufacturing)是一种全新的制造理念,它从电子商务和敏捷供需链的角度将制造工厂和车间与企业管理系统进行集成,从而降低生产成本、提高生产效率。该文介绍了e-Manufacturing的基本概念及其体系结构,论述了e-Manufacturing与数字化制造的区别与联系,分析了适合我国国情的e-Manufacturing实施策略。     

Classification and Concept Consistency

Abstract

This article investigates the extent to which undergraduates consistently use a single mechanism as a basis for classifying mathematical objects. We argue that the concept image/concept definition distinction focuses on whether students use an accepted definition but does not necessarily capture the more basic notion that there should be a fixed basis for classification. We examine students’ classifications of real sequences before and after exposure to definitions of increasing and decreasing; we develop an abductive plausible explanations method to estimate the consistency within the participants’ responses and suggest that this provides evidence that many students may lack what we call concept consistency.     

Queries and Concept Learning

We consider the problem of using queries to learn an unknown concept. Several types of queries are described and studied: membership, equivalence, subset, superset, disjointness, and exhaustiveness queries. Examples are given of efficient learning methods using various subsets of these queries for formal domains, including the regular languages, restricted classes of context-free languages, the pattern languages, and restricted types of propositional formulas. Some general lower bound techniques are given. Equivalence queries are compared with Valiant's criterion of probably approximately correct identification under random sampling.