一种面向主题的Web知识检索方法

知识检索研究如何从数据和信息中抽取知识.在数据和信息日益增长的今天,知识检索显得尤为重要.现有的知识检索主要以事先构造好的知识库为基础,需要通过专家来构建和维护用于检索的知识库.然而,人工构建知识库非常耗时而且代价很高,而且,基于事先构造好的知识库的检索结果也被局限于知识库覆盖的范围,不具有动态性和时变性.本文提出了一种基于Web的面向主题的知识检索方法.该方法一方面以开放动态的Web信息为基础,支持动态即时的知识检索;另一方面,以用户选定的主题为中心,从Web信息中动态获取知识,构成与用户主题相关的知识检索结果,不局限于某个特定领域.     

一种面向主题的web知识检索方法

知识检索研究如何从数据和信息中抽取知识,在数据和信息日益增长的今天,知识检索显得尤为重要。现有的知识检索主要以事先构造好的知识库为基础,需要通过专家来构建和维护用于检索的知识库。然而,人工构建知识库非常耗时而且代价很高,而且,基于事先构造好的知识库的检索结果也被局限于知识库覆盖的范围,不具有动态性和时变性。本文提出了一种基于Web的面向主题的知识检索方法。该方法一方面以开放动态的Web信息为基础,支持动态即时的知识检索;另一方面,以用户选定的主题为中心,从Web信息中动态获取知识,构成与用户主题相关的知识检索结果,不局限于某个特定领城。     

专家系统中知识表示法研究

专家系统的特征之一是知识性,而造就它的关键技术在于知识的表示,知识的获取和知识的应用,知识的表示方式是至关重要的,它不仅决定了知识应用的形式,而且也决定了知识处理的效率和实现的域空间规模的大小, 成功与否直接关系到智能系统的水平。本文仅对知识表示法进行讨论。     

诊断专家系统知识表示方法研究

根据故障诊断领域专家知识结构，本文设计了一种适用于诊断类专家系统的知识表示方法，并在微型计算机故障诊断专家系统中得到应用，效果良好。     

层次链专家系统方法在工资审批中的应用

文章介绍了将层次链专家系统方法应用于工资审批系统中工资审批计算过程,给出了层次链知识建模、知识表示的基本构架,描述了对属性、产生式规则和基于案例的推理流程,解决了工资计算的复杂性、多变性以及扩充性问题。     

基于浅层知识和深层知识推理的故障诊断专家系统工具

以专家系统和诊断问题求解为基础，建立了基于浅层知识和深层知识推理相结合的故障诊断专家系统工具。文中论述了工具的结构、知识表示、参数设计、推理机制、黑板控制、学习机制和其它支持环境。     

营销管理专家系统中的知识问题

知识和概念化是专家系统设计与实现中的核心难题,对于领域开放、任务非受限的复杂应用而言,知识的细致充分性和知识形式的匹配有效性是解决诸如营销管理专家系统设计与实现这样现实应用时必然面临的问题。本文详细定义了这样两个问题是什么,它们是如何产生的,并且讨论了解决问题的方法。     

POADES知识库的构建

提出面向问题分析与决策专家系统的知识库构建方法,并用于公路工程质量问题智能分析与诊断专家系统开发。以问题为核心,根据关键的基本对象、问题对象、问题现象对象、原理知识对象和过程知识对象(MP4对象)对知识进行筛选,实现知识领域化,对其进行抽象和分类得到层次化表示的问题对象树,以问题对象树为依据构建知识字典和知识关系。结果证明该方法可以较快地建立知识库。     

面向问题分析与决策的专家系统

专家系统的根本目标在于为实际应用问题提供强有力的分析与决策能力。以人类通过长期实践活动总结的复杂问题分析与决策方法为指导思想,建立了以问题对象为核心、相关对象为问题主体、问题现象为表现形式、因果关系为问题变化驱动力、过程知识和原理知识为参考对象的面向问题分析与决策的专家系统。这种专家系统围绕应用领域中的问题构建知识库,而不是使用规则,所以得到的知识系统比较合理、清晰,不容易产生知识矛盾与冲突,有利于大型知识库的构建;同时,采用基于问题的推理,与人类的思维习惯相符合,可以大大提高推理效率;此外,开发这种专家     

An expert intermediary system for interactive document retrieval

Constructing natural language interfaces to computer systems often requires achievement of advanced reasoning and expert capabilities in addition to basic natural language understanding. In this paper the above issue is tackled in the frame of an actual application concerning the design of a natural language interface for interactive document retrieval. After a short discussion of the peculiarities of this application, which requires both natural language understanding and reasoning capabilities, the general architecture and fundamental design criteria of a system presently being developed at the University of Udine are presented. The system, named IR-NLI, is aimed at allowing non-technical users to directly access through natural language the services offered by online databases. Attention is later focused on the basic functions of IR-NLI, namely understanding, dialogue and reasoning. An example of interaction with IR-NLI is fully worked out to introduce the main features of the system. Knowledge representation methods and algorithms adopted are then illustrated. Perspectives and direction for future research are also discussed.     

Implementing a fuzzy expert system for ensuring information technology supply chain

In the business environment, information technology (IT) plays an important role for firms' performance. It provides information flow that makes the supply chain more robust and resilient without undermining its efficiency. Smart systems use artificial intelligence methods for solving problems and facilitating decision‐making through rule‐based deduction. Accordingly, these systems can present specialists' skills and simulate their thinking process. The primary goal of expert systems is to implement knowledge acquisition process by converting knowledge to wisdom. This process is vital for critical decision‐making regarding important issues such as determining necessities of a particular contract. Companies use professional liability insurance of the products and services to ensure the purchasers and prevent potential losses. Although this practice is highly prevalent, there is not any particular procedure for measuring necessities of contracts. The main purpose of this paper is to design a fuzzy expert system for measuring the necessities of professional contracts regarding insurance coverage and improve the supply chain management using IT. This system can measure and report these obligations, considering specifications of each project. Taking into perspective variety of professional services/products, we consider software as a type of professional contracts, extract its important indices and give it to the system as the input. After the necessary stages, the system produces a proper response and presents the generated response to the user. The software of this expert system is web based, and there are four operating layers in its architecture. We implemented this program in MS Visual Studio Framework with C#.NET programming language. Moreover, we implemented MS SQL‐Server Database Management.     

投资项目管理的知识支持系统

从系统工程角度分析投资项目管理，针对建设投资项目系统存在的不确定性，提出建立了一个对整个投资项目管理周期的市场环境和企业的生产经营信息进行存储管理的知识库，用来辅助企业做出各种决策。采用面向对象技术构造知识库开发模型，给出了相应的模型结构，建立了现实性校验流程图，知识支持系统自始至终优化管理建设投资项目，增强了决策信息的可靠性，使项目投资最优化。     

地质分析专家系统GAES的设计

地质分析是一项复杂的人类劳动,采用人工智能技术模拟人类专家活动,可以大大减轻人类的负担.因此,开发了一个地质分析专家系统GAES.该系统以黑板模型为基础,采用分布式系统结构,在中心节点的协调控制下,各普通节点相互合作,共同进行问题求解.在系统技术特点方面,解决了知识源分配、冲突消解和知识源筛选等问题,该系统具有求解效率高、可靠性强、通讯机制好等特点.     

Knowledge Acquisition Advisor (KA): An interactive knowledge-acquisition tool for expert system development

A new interactive knowledge acquisition tool, called Knowledge Acquisition Advisor (KA²), is presented in this paper. The new tool will help knowledge engineers to conduct effective knowledge-elicitation interviews with domain experts through structured knowledge acquisition for both analytic and synthetic problems. A graphic modeling data structure, called Knowledge Graph is proposed, which allows knowledge engineers to model domain problems with their images and understanding. By using Knowledge Graph, knowledge engineers are able to decompose a domain problem into several components, to model the feature of each component, and to explore their relations by linking them with sets of questions. These questions can later be employed to guide the KA interview. Moreover, KA² is particularly useful for interview through computer networks, so the knowledge acquisition can take place remotely.     

基于模糊框架-产生式知识表示及推理研究

知识表示是专家系统求解能力及正确性的基础。针对不同知识表示方法的局限性,采用框架与产生式知识表示法结合表示专家知识。同时鉴于传统知识表示及推理方法在描述事实生产中不确定知识及经验中的缺陷问题,将模糊推理与知识表示相结合,应用模糊因子,定量细化描述模糊知识;并结合知识表示特点应用动态加权平均匹配函数及模糊推理方法,提出基于模糊框架-产生式知识表示方法及推理的研究,量化地表示知识及推理过程,为决策人员提供更加直观、准确的推理依据。     

Comparing response latency and self-report methods for estimating levels of certainty in knowledge elicitation for rule-based expert systems

Many practitioners and theoreticians feel uncomfortable in using classic self‐report, knowledge acquisition methods for assessing an expert’s feelings of confidence or certainty about rules, choices or decisions. This paper proposes and tests an alternative approach using response latency, or the time it takes an expert to respond to a paired choice inquiry. The question is to learn if there is any merit in considering the response latency approach as a replacement for the classic method. This investigation is concerned with using the analytic hierarchy process (AHP) to compare two methods for estimating a subject’s feeling of certainty or confidence about their rule, choice or decision. One method is the older or classic method where a subject self‐reports both the choice selected and the level of certainty associated with a choice‐pair on the 1‐to‐9 scale used with the AHP. The second is proposed by the authors and based on using only the choice and decision time or response latency. In the second case, the inverse of response latency is used to estimate a subject’s degree of certainty or confidence in the selected choice in a paired comparison experiment. The response latency method has the advantage of being unobtrusive, less prone to conscious censure, quicker to perform, requiring less effort, and possibly being less expensive to administer. Employing AHP methodology, priorities are used to represent the degree of confidence among choices or rules, and consistency ratios are used to estimate the degree of consistency detected by each method. To compare the two methods, 21 subjects were evaluated in a paired sample design. Employing a computer‐administered questionnaire, subjects expressed relative levels of confidence for a set of potential recommendations and the time for each subject to respond was recorded unobtrusively. Using paired sample t tests, sufficient evidence was found to reject the null hypothesis (α= 0.025) that the mean of the difference in the priorities between the two methods was zero (p < 0.0001). In a second test, there was sufficient evidence to be at least 95% confident of accepting an alternative hypothesis that response latency produces a lower consistency ratio (higher consistency of the reports) than the self‐report method (p < 0.0001). In addition to the tests of significance, the results were found to be practically significant and are discussed in the paper.