两大类形式化方略

阐述机器翻译的两大类形式化方略。其中,第一大类形式化方略涉及:编程语言和英语(自然语言);第二大类形式化方略涉及:二进制数与十进制数、十进制数与汉字中文、中文和英文(可换)三类双语协同变换,属于形式化及其拓展研究领域。其结果是:凸显了第二大类形式化方略。其意义是:揭示了其理论依据,并为含语言学在内的学科知识系统工程提供了广义双语信息处理技术,有利于母语为非英语的计算机用户改善人机对话的语言环境。     

间接计算模型和间接形式化方法

本文旨在从人机交互界面与协同计算程序结合而构成协同智能计算系统的角度,论述间接计算模型和间接形式化方法结合所支持的优化云计算技术原理。本文在系统回顾图灵可计算理论、克莱尼小字符串形式理论、冯诺依曼数字计算机体系结构和图灵人工智能判定假设等前人理论研究成果对主流数字计算机通用范式影响的基础之上,着重介绍了笔者设计的间接计算模型和大、小字符串兼容的问接形式化理论,并以中文信息数据为例介绍了协同智能计算系统原型的设计构想。其意义是该成果有利于从数据中心到知识中心优化云计算。     

虚拟的孪生图灵机——以双语信息处理为例

本文阐述一种虚拟的孪生图灵机,即：由两个图灵机组成的孪生并行计算机,其特征是其受限模式与派生模式分别由汉语的言即单音节字的基本符号对象和语即双音节多音节字组的符号组合解释为例加以说明。其作用在于基于它可建构理想的双语信息处理系统,即：协同智能计算系统;应用它可形成并行计算、分布计算、网格计算、虚拟计算和云计算乃至超级计算。其意义在于借助它蕴含的协同智能计算本质——虚拟与现实的关系,可把图灵可计算性、计算复杂性（其中揭示了一个基本原理——NP=P当且仅当N可有可无）和图灵测试连贯起来。     

利用智能引导和KDML增强可拓模型人机建模能力研究

为了利用计算机协助人们建立待求解问题的可拓模型,必须让计算机识别用自然语言描述的问题,而且要理解问题的含义,这是相当困难的任务。本文提出利用人机界面Agent的智能引导并结合知网（HowNet）中的知识系统描述语言（KDML）,增强计算机语义处理能力的方法。以求职问题为实践的结果说明了方法的有效性。由于KDML有较强的表示语义信息的作用,通过人机交互也能减轻计算机自然语言理解的困难。因此该方法能将自然语言描述的待求解问题的目标和条件进行分离和形式化,使计算机更有效地建立待求解问题的可拓模型。     

软件工程学科何以独特——形式化方法的双重路径

本文旨在以数字和文字双语信息处理为例论述软件工程的第二路径及其重要意义。具体涉及如下两个问题及其解答：第一,软件工程学科何以独特？在其解答过程中进一步提出了软件工程的双重路径问题;第二,软件工程的第二路径为什么显著优于第一路径？其中预示软件产业将由此重组。从方法论的角度来看,前者涉及协同智能观;后者涉及第二路径的论证。从学科体系的角度来看,涉及软件的两次定位。其中,如果说第一次是计算机软件产品脱胎于数学和语言学,那么,第二次就是软件工程服务脱胎于计算机学科和信息学及其相关的工程技术学科和管理学以及教育学的相关部分。前一轮形成了软件产品概念,后一轮形成了软件服务概念。这是一个系统工程,其特点是整体大于局部之合。在此,就是虚拟的自然入（设计者和用户）与虚拟的计算机（操作系统和应用系统以及其它各式各样的软件）各自的功能,均不及两者结合而成的协同智能计算系统的整合功能。     

基于粗糙集的间接学习

粗糙集理论为处理不精确、不确定数据提供了一个新的数学方法,已被广泛应用于人工智能、模式识别与智能信息处理等计算机领域。在Pawlak粗糙集模型中,等价关系起着至关重要的作用。任意给定一个概念(论域的子集),人们不一定能用知识库中的知识(等价类)来精确地描述,这时就用关于这个概念构成的集合的一对上、下近似来描述。但是,对等价关系的严厉要求限制了粗糙集理论的应用,因此许多学者从各方面对Pawlak粗糙集模型作了推广。     

双语信息处理方法及原理

旨在阐述双语信息处理方法及其原理。该方法的特征在于人机双方都可按各自的特点来彼此协作或响应,具体含三个基本步骤:首先,从汉英翻译的困难发现问题;接着从跨学科、跨领域和跨行业的角度分析问题;最后,从人机分工与合作的角度解决问题。其结果是,不仅发现了大、小字符串并行的双重形式化进路,而且还发现并验证了广义双语信息处理方法的优点及其所遵循的科学原理。其意义在于:既可从理论上开阔思路,又可在实践中发挥作用。例如可兼容形式信息论的收敛性或封闭性与语义信息论的发散性或开放性;再如可采用算术和语文这样的广义双语信息处理方法驾驭强、弱两派的人工智能观点。不仅可很好地解释信息术语的约束条件,而且还可较为满意地规范不同的信息观和人工智能观的应用约束情景即兼顾人际、人机、机际、机人一系列双语应用的实际语境。     

面向主题的信息抽取需求描述与分析

在构建面向主题的信息抽取系统时,抽取需求是明确抽取任务的前提。针对自然语言描述的抽取需求导致计算资源浪费与抽取效率降低的问题,提出面向主题的信息抽取需求的形式化定义,并研究抽取需求之间的关系。采用精简需求集拆分的方法构造等价精简需求集,消除多抽取需求之间存在的冗余。实验结果证明,等价精简需求集能够提高多需求抽取任务的运行效率。     

基于双语词汇Web间接关联的无指导译文消歧

为解决困扰词义消歧及译文消歧任务中存在的数据稀疏及知识获取问题,提出一种利用双语词汇Web间接关联的完全无指导消歧方法.首先做出词汇歧义可由双语词汇的间接关联度决定的假设,为译文消歧提供了一种新的知识.在此基础上,对4种常用计算间接关联的方法进了改造并定义了双语词汇Web间接关联.随后进行基于Web的词汇消歧知识获取并设计了3种消歧决策方法.最后,在国际语义评测SemEval-2007中的Multilingual Chinese English Lexical Sample Task测试集进行了测试.该方法的P_mar值为44.4%,超过了该评测上最好的无指导系统的结果.     

基于领域知识的个性化协同商务推荐系统

基于领域知识与顾客购买倾向相关联的事实,从知识表示、知识获取、系统实现三个方面研究了个性化协同商务推荐系统的实现策略。知识表示研究了自然语言的本体表示,主要包括：知识本体描述、模糊关系设计、概念关联抽象和公理修正四个部分;知识获取采用多层次领域知识获取和基于数据挖掘的智能知识获取两种方法,对知识的形式化和结构化进行了研究;基于J2EE技术创建了由客户端、服务器端、存储系统组成的协同商务推荐系统的结构模型。最后通过测试网站对系统的有效性进行了验证。     

Toward Better Understanding and Use of Business Intelligence in Organizations

This article provides valuable information on the chances and the possibilities of Business Intelligence applying in organizations. Three theories—the Resource-Based View, Maturity Models, and Critical Success Factors—were used to investigate Business Intelligence issues. They provided a comprehensive view on Business Intelligence. Using a semi-structured interview method, the results from 20 organizations applying Business Intelligence are presented. Finally, based on the analysis of the literature and on the qualitative surveys, conclusions for future research in Business Intelligence are provided.     

A multidisciplinary course based on social intelligence design and collaborative learning

This paper presents the experience of applying the Social Intelligence Design (SID) paradigm in a multidisciplinary course planned with Collaborative Learning (CL). Through the experience, three levels of SID were discovered; one was the social product/artifact, the other two were the student’s social process and the professor’s social process. Authors propose a framework for SID-based education and CL as a possible tool for supporting and assessing such experiences. The experience of this approach seems very promising for social product innovation, social entrepreneurship, and social awareness.     

脑与认知科学主动学习教学研究

针对智能科学与技术专业脑与认知科学课程教学实际,在分析专业特色、课程特点的基础上,阐述教师课堂讲授、实验创新教学与学生主动学习实践相结合的观点。大连海事大学智能科学与技术专业2009级教学实际表明,脑与认知科学课程主动学习在教学中取得良好效果。     

基于曼哈顿距离加权协同表示分类的车辆识别

加权稀疏表示分类（WSRC）在声频传感器网络下的车辆识别中取得了不错的效果。但是稀疏表示分类（SRC）中实际上起较大作用的是字典中所有类的协同表示,因此协同表示分类（CRC）被提出用来提升算法效率,CRC框架还改进了残差计算方式来提高识别精度。在WSRC中发现保局性对提升识别率起到很好的作用,因此在CRC中引入加权编码,提出了声频传感器网络下基于加权协同表示分类（WCRC）的车辆识别方法,取得了明显的速度（相比WSRC、SRC）以及不错的精度（对比WSRC、CRC、SRC）提升。同时针对欧氏距离对样本相似性判断的不足,将曼哈顿距离引入加权编码,进一步地提出了基于曼哈顿距离加权协同表示分类（Manhattan-WCRC）的车辆识别方法,取得了最高的识别率,而运算速度与WCRC接近。     

中远程舰空导弹协同制导飞行试验安控方案设计

针对中远程舰空导弹协同制导飞行试验的实施安全性问题,对舰空导弹协同制导作战过程和舰空导弹安全控制措施进行了分析,提出了中远程舰空导弹协同制导飞行试验安控基本方案;重点对安控系统组成、安全管道设置及导弹自毁残骸落点估算、安控工作流程、安控软件方案等关键内容进行了研究;该方案设计基于单舰制导导弹飞行试验安全控制实践经验,紧贴试验工程实际,对于中远程舰空导弹协同制导飞行试验的的安全实施具有较好的实用价值和参考意义。     

Achieving a sustainable interoperability of standards

Agile enterprises and networks are required to continuously evolve so as to adequately respond to a dynamic, global and very competitive business environment. Unfortunately, this continuous change requirement affects the capacity of the enterprise to effectively interoperate internally and externally. Adding to this problem, the standards typically used as pillars for enterprise and network management and (inter)operation are themselves subject to continuous change and often bring their own interoperability, inconsistency and overlap problems. It is essential that such concerns are identified and addressed in a sustainable manner, i.e. taking into account the life cycles of all entities involved as their interoperability capabilities and requirements change along their lives. This paper focuses on interoperability issues specific to standards and proposes a novel and original way forward based on principles tested in previous case studies combining elements from the Enterprise Interoperability, Architecture and Integration, Collaborative Networks and Artificial Intelligence bodies of knowledge.     

关于知识表示的讨论

知识表示是人工智能（ＡＩ）研究中基本问题之一,对ＡＩ来说,知识表示的研究分成两个层次：（２）知识表示方法的研究,（２）表示观的研究,首先,本文在总结各种表示方法的基础上,提出了一种“知识表示体系树”,以观察ＡＩ研究的发展趋势,其次,文中收集了目前ＡＩ学界对这个问题讨论了各种主张,并将其归纳为评论论、本体论及知识工程等三类对表示的观点;最后,还讨论了ＡＩ一些研究分支与表示的关系。     

A Prolog simulator for deterministic P systems with active membranes

In this paper we propose a new way to represent P systems with active membranes based on Logic Programming techniques. This representation allows us to express the set of rules and the configuration of the P system in each step of the evolution as literals of an appropriate language of first order logic. We provide a Prolog program to simulate, the evolution of these P systems and present some auxiliary tools to simulate the evolution of a P system with active membranes using 2-division which solves the SAT problem following the techniques presented in Reference.¹⁰ Andrés Cordón-Franco: He is a member of the Department of Computer Science and Artificial Intelligence at the University of Sevilla (Spain). He is also a member of the research group on Natural Computing of the University of Seville. His research interest includes Mathematical Logic, Logic in Computer Science, and Membrane Computing, both from a theoretical and from a practical (software implementation) point of view. Miguel A. Gutiérrez-Naranjo: He is an assistant professor in the Computer Science and Artificial Intelligence Department at University of Sevilla, Spain. He is also a member of the Research Group on Natural Computing of the University of Seville. His research interest includes Machine Learning, Logic Programming and Membrane Computing, both from a theoretical and a practical point of view. Mario J. Pérez-Jiménez, Ph.D.: He is professor of Department of Computer Science and Artificial Intelligence at University of Seville, where he is the head of the Group of Research on Natural Computing, He has published 8 books of Mathematics and Computation, and more than 90 scientific articles in prestigious scientific journals. He is member of European Molecular Computing Consortium. Fernando Sancho-Caparrini: He is a member of the Department of Computer Science and Artificial Intelligence at the University of Sevilla (Spain). He is also a member of the research group on Natural Computing of the University of Seville. His research interest includes Complex Systems, DNA Computing, Logic in Computer Science, and Membrane Computing, both from a theoretical and from a practical point of view.     

Lewis Carroll's contributions to artificial intelligence

Lewis Carroll, author of “Alice in Wonderland”, wrote about “Symbolic Logic”, which is equivalent to Propositional or Predicate Logic used in Artificial Intelligence today. He used logical symbols such as negation, conjunction, implication plus logical charts to solve problems. This study will present his contributions to Artificial Intelligence today.     

Collaborative sense-making during simulated Intelligence Analysis Exercises

Sense-making plays an important role in Intelligence Analysis, but can be difficult to study in situ. Thus, it is useful to exploit training exercises to study this phenomenon. In this paper two versions of the same exercise are reported: one undertaken by participants at a conference and one undertaken by Military Intelligence personnel. The behaviour of groups of analysts (experienced versus inexperienced) is considered in terms the Data/Frame model of sense-making. The paper illustrates how Intelligence Analysis often involves parallel and overlapping explorations of data, with multiple frames that might be minimal and sketchy. The use of representations, such as link diagrams, provides a means of externalising frames and it is suggested that these can shift the style of reasoning exhibited by the teams as the Exercise progresses. Such a shift was seen more clearly in the behaviour of the Military Intelligence Officers who also spent more time developing and refining the diagrams to support the presentation of their findings.