基于语义表示的数据仓库构建方法

介绍了基于语义的数据仓库的构建方法，给出了3层数据加工流程的数据加工实例，在基于语义的数据仓库技术基础上，提出了一种新的支持模糊查询的模糊数据的管理方法，将其应用于某烟草销售企业数据仓库的构建，取得了较好的效果。     

语言变量模糊本体的表示与构建

语言变量模糊本体是语言变量在语义Web中的明确的规范化说明,有利于模糊系统与语义Web的结合,使得语义web更加方便地处理模糊信息。通过引入语言变量模糊本体的概念,研究使用RDF表示模糊本体的方法,将本体与模糊概念表示为“资源”。进而以工业洗衣机的模糊控制为例,提出从模糊系统构造语言变量模糊本体的过程。     

基于语义表示的数据仓库构建方法

介绍了基于语义的数据仓库的构建方法,给出了3层数据加工流程的数据加工实例,在基于语义的数据仓库技术基础上,提出了一种新的支持模糊查询的模糊数据的管理方法,将其应用于某烟草销售企业数据仓库的构建,取得了较好的效果.     

表象式直接知识表示

通过对人的相对低层次认知行为的模仿可以改善计算机感知外部世界的能力。知觉作为首要的认知行为,它所需要的知识不便于采用传统的符号化知识表示方法来表示。该文以视知觉研究为基础,通过模拟分布于视皮层中的特异性功能柱型结构,将图形模式分解为简单特征的组合,直接表示在神经网络上,众多功能单元的同时响应就构成某一实体的视觉表象。最后还讨论了这种直接知识表示方法在知识与概念化问题、知识的来源问题、学习问题等几个最核心的人工智能问题下的意义。     

Computing the Numerical Scale of the Linguistic Term Set for the 2-Tuple Fuzzy Linguistic Representation Model

When using linguistic approaches to solve decision problems, we need the techniques for computing with words (CW). Together with the 2-tuple fuzzy linguistic representation models (i.e., the Herrera and MartÍnez model and the Wang and Hao model), some computational techniques for CW are also developed. In this paper, we define the concept of numerical scale and extend the 2-tuple fuzzy linguistic representation models under the numerical scale. We find that the key of computational techniques based on linguistic 2-tuples is to set suitable numerical scale with the purpose of making transformations between linguistic 2-tuples and numerical values. By defining the concept of the transitive calibration matrix and its consistent index, this paper develops an optimization model to compute the numerical scale of the linguistic term set. The desired properties of the optimization model are also presented. Furthermore, we discuss how to construct the transitive calibration matrix for decision problems using linguistic preference relations and analyze the linkage between the consistent index of the transitive calibration matrix and one of the linguistic preference relations. The results in this paper are pretty helpful to complete the fuzzy 2-tuple representation models for CW.      

Combination of Qualitative Information with 2-Tuple Linguistic Representation in DSmT

Modern systems for information retrieval,fusion and management need to deal more and more with information coming from human experts usually expressed qualitatively in natural language with linguistic labels.In this paper,we propose and use two new 2-Tuple linguistic representation models(i.e.,a distribution function model(DFM) and an improved Herrera-Martínez's model) jointly with the fusion rules developed in Dezert-Smarandache Theory(DSmT),in order to combine efficiently qualitative information expres...     

Task-Action Grammars: A Model of the Mental Representation of Task Languages

A formal model of the mental representation of task languages is presented. The model is a metalanguage for defining task-action grammars (TAG): generative grammars that rewrite simple tasks into action specifications. Important features of the model are (a) Identification of the "simple-tasks" that users can perform routinely and that require no control structure; (b) Representation of simple-tasks by collections of semantic components reflecting a categorization of the task world; (c) Marking of tokens in rewrite rules with the semantic features of the task world to supply selection restrictions on the rewriting of simple-tasks into action specifications. This device allows the representation of family resemblances between individual task-action mappings. Simple complexity metrics over task-action grammars make predictions about the relative learnability of different task language designs. Some empirical support for these predictions is derived from the existing empirical literature on command language learning, and from two unreported experiments. Task-action grammars also provide designers with an analytic tool for exposing the configural properties of task languages.     

Rule Base Reduction and Genetic Tuning of Fuzzy Systems Based on the Linguistic 3-tuples Representation

Recently, a new linguistic rule representation model was presented to perform a genetic lateral tuning of membership functions. It is based on the linguistic 2-tuples representation model, that allows the symbolic translation of a label considering an unique parameter. It involves a reduction of the search space that eases the derivation of optimal models. This work presents a new symbolic representation with three values (s, α, β), respectively representing a label, the lateral displacement and the amplitude variation of the support of this label. Based on this new representation we propose a new method for fine tuning of membership functions that is combined with a rule base reduction method in order to extract the most useful tuned rules. This approach makes use of a modified inference system that consider non-covered inputs in order to improve the final fuzzy model generalization ability, specially in highly non-linear problems with noise points. Additionally, we analyze the proposed approach showing its behavior in two real-world applications. Supported by the Spanish Ministry of Science and Technology under Projects TIC-2002-04036-C05-01 and TIN-2005-08386-C05-01.     

The Feasibility of Incremental Linguistic Annotation

This paper examines the feasibility of incremental annotation, i.e. using existing annotation on a text as the basis for further annotation rather than starting the new annotation from scratch. It contains a theoretical component, describing basic methodology and potential obstacles, as well as a practical component, describing an experiment which tests the efficiency of incremental annotation. Apart from guidelines for the execution of such pilot experiments, the experiment demonstrates that incremental annotation is most effective when supported by thorough pre-planning and documentation. Unplanned, opportunistic use of existing annotation is much less effective in its reduction of annotation time and furthermore increases the development time of the annotation software, so that this type of incremental annotation appears only practical for large amounts of heritage data.     

The Locally Nameless Representation

This paper provides an introduction to the locally nameless approach to the representation of syntax with variable binding, focusing in particular on the use of this technique in formal proofs. First, we explain the benefits of representing bound variables with de Bruijn indices while retaining names for free variables. Then, we explain how to describe and manipulate syntax in that form, and show how to define and reason about judgments on locally nameless terms.     

The Representation of Fuzzy Knowledge

Abstract

A new AI programming language (called FUZZY) is introduced which provides a number of facilities for efficiently representing and manipulating fuzzy knowledge. A fuzzy associative net is maintained by the system, and procedures with associated “procedure demons” may be defined for the control of fuzzy processes. Such standard AI language features as a pattern-directed data access and procedure invocation mechanism and a backtrack control structure are also available.

This paper examines some general techniques for representing fuzzy knowledge in FUZZY, including the use of the associative net for the explicit representation of fuzzy sets and fuzzy relations, and the use of “deduce procedures” to implicitly define fuzzy sets, logical combinations of fuzzy sets, linguistic hedges, and fuzzy algorithms. The role of inference in a fuzzy environment is also discussed, and a technique for computing fuzzy inferences in FUZZY is examined.

The programming language FUZZY is implemented in LISP, and is currently running on a UNIVAC 1110 computer.     

The Computational Origin of Representation

Minds and Machines - Each of our theories of mental representation provides some insight into how the mind works. However, these insights often seem incompatible, as the debates between symbolic,...     

A Life or Death InfoSec Subversion

Details about failures of complex and well-implemented information-based attacks on systems are extremely difficult to obtain. However, here the authors examine a real-life analogue - an information attack on a highly complex security system, that of the Colombian guerrilla group FARC. This operation included a man-in-the-middle attack, targeted denial of service (DoS), and authentication subversion. The attack on FARC's communications structure is interesting not only because of its electronic and analog components, but also because it was a life or death matter. The authors examine the hostages' liberation from an information security perspective, compiling data from several Colombian newspapers and magazines and using the most accepted version of the events.     

Drivers' Mental Representation of Travel Time and Departure Time Choice in Uncertain Traffic Network Conditions

The decisions drivers make, such as choice of route or departure time, constitute typical decision making under uncertainty. Drivers' decision making has been studied within the framework of expected utility theory. However, empirical decisional phenomena violating the premise of expected utility theory have been observed repeatedly. These findings have indicated that decision making is critically affected by the decision frame. It has also been pointed out that the uncertainty of outcome is perceived as an interval of possible resultant values. Based on these findings, we propose hypotheses that: (1) a driver perceives an uncertain travel time as an interval, and (2) a driver decides on a departure time based on a decision frame edited by this interval. To test these hypotheses, we collected data on drivers' departure time choice behavior, n = 335. Decisional phenomena found in this study confirm our hypotheses.     

Internal Representation of Task Structure and Mental Load of Work: Approaches and Methods of Assessment

Abstract

A survey is presented of research designed to elucidate problems of mental load in industrial work, using both laboratory experiments and field studies, and examining relationships between the mental demands of jobs and changes during a working spell of various indices of performance and of subjective and physiological effects. An initial enunciation of general principles stresses the importance of internal models, strategies and goals in the organisation of work activities. This is followed by brief accounts of four experimental studies. Of these, one showed that the effects of load are multidimensional, a second gave evidence of shifts of aspiration and motivation, a third illustrated the value of adequate internal models as a means of preventing fatigue, and a fourth indicated that job enrichment which increases the mental demands made by industrial work need not produce undue mental load.     

继承、颠覆与超越——计算摄影

计算摄影是利用计算机及软件方法结合现代传感器、现代光学等技术创造出新型摄影设备及应用的综合技术.计算摄影在继承已有摄影技术的基础上,通过对传统摄影技术中各个部件、工作过程甚至是原理上的改进与革新,突破了现有摄影技术的种种限制,成为摄影技术的又一次革命.计算摄影是一个涉及众多学科的交叉研究领域,针对同一个问题有很多不同的角度和方法.为了全面了解计算摄影这个新兴领域,以计算相机原理为线索,从计算场景、计算光学、计算传感器以及计算处理4个方面介绍了计算摄影研究的热点问题和实例.最后总结了目前计算摄影现状及发展趋势.     

The Linguistic Design of the EuroWordNet Database

In this paper the linguistic design of the database under construction within the EuroWordNet project is described. This is mainly structured along the same lines as the Princeton WordNet, although some changes have been made to the WordNet overall design due to both theoretical and practical reasons. The most important reasons for such changes are the multilinguality of the EuroWordNet database and the fact that it is intended to be used in Language Engineering applications. Thus, i) some relations have been added to those identified in WordNet; ii) some labels have been identified which can be added to the relations in order to make their implications more explicit and precise; iii) some relations, already present in the WordNet design, have been modified in order to specify their role more clearly.     

互联网，正在颠覆时代

科学技术是生产力,这是马克思主义历来的观点。早在一百多年前,马克思就说过,机器生产的发展要求自觉地应用自然科学。一个时代的科学技术不仅是那个时代发展生产力最活跃的因素,也必然是那个时代先进文化的代表。     

产品配置的知识表示

为按照用户的需要定制售卖产品的公司提供支持的基于知识的配置系统,产品配置器是人工智能技术的一个重要应用.本文首先描述了配置问题及其相关概念,然后分析了某些配置知识表示的优缺点,在此基础上提出了产品配置知识的图形表示方法,最后讨论了目前的一些热点研究问题.     

粗糙模糊集的近似表示

粗糙模糊集是利用粗糙集的 Pawlak 知识空间来近似刻画一个模糊集（不确定概念）的理论模型．粗糙模糊集用上、下近似模糊集作为目标概念的边界模糊集,它没有给出在当前知识基下如何得到目标模糊概念的近似模糊集或近似精确集的方法．文中首先给出模糊集的相似度（近似度）的概念,定义了 Pawlak 知识空间U／R 下的阶梯模糊集、均值模糊集、0．5-精确集等概念;然后分析得出U／R 知识空间下的均值模糊集是所有阶梯模糊集中与目标模糊集最接近的模糊集,U／R 知识空间下0．5-精确集是目标模糊集最接近的近似精确集;分析了均值模糊集、0．5-精确集分别与目标模糊集之间的相似度随知识粒度变化的变化规律．从新的视角提出了不确定性目标概念的近似表示和处理的方法,促进了不确定人工智能的发展．