Distributed knowledge acquisition for the automatic construction of integrated expert systems

The authors discuss the problem of distributed knowledge acquisition for the construction of complete and consistent databases in integrated expert systems via the sharing of knowledge sources of different topologies (experts, problem-oriented texts, and electronic media in the form of databases). The emphasis is on the models, methods, and algorithms of distributed knowledge acquisition from databases as additional knowledge sources. The authors describe the architecture and basic facilities of distributed knowledge acquisition, which function as a part of the AT-TECHNOLOGY tool complex.     

Discriminative probabilistic models for expert search in heterogeneous information sources

In many realistic settings of expert finding, the evidence for expertise often comes from heterogeneous knowledge sources. As some sources tend to be more reliable and indicative than the others, different information sources need to receive different weights to reflect their degrees of importance. However, most previous studies in expert finding did not differentiate data sources, which may lead to unsatisfactory performance in the settings where the heterogeneity of data sources is present. In this paper, we investigate how to merge and weight heterogeneous knowledge sources in the context of expert finding. A relevance-based supervised learning framework is presented to learn the combination weights from training data. Beyond just learning a fixed combination strategy for all the queries and experts, we propose a series of discriminative probabilistic models which have increasing capability to associate the combination weights with specific experts and queries. In the last (and also the most sophisticated) proposed model, the combination weights depend on both expert classes and query topics, and these classes/topics are derived from expert and query features. Compared with expert and query independent combination methods, the proposed combination strategy can better adjust to different types of experts and queries. In consequence, the model yields much flexibility of combining data sources when dealing with a broad range of expertise areas and a large variation in experts. To the best of our knowledge, this is the first work that designs discriminative learning models to rank experts. Empirical studies on two real world faculty expertise testbeds demonstrate the effectiveness and robustness of the proposed discriminative learning models.     

Linked-learning for knowledge acquisition: a pilot's associate case study

We developed a knowledge acquisition system that uses an Explanation-Based Learning domain theory as a knowledge repository from which general knowledge structures can be compiled and then translated by smart translators into the various specialized representations required for the separate expert system modules of a distributed pilot aiding system. We call this two-stage learning-plus-translation process linked learning. This architecture addresses learning for multiple modules with different knowledge representations and performance goals, but which must all perform together in an integrated fashion. It also addresses learning for an intelligent agent which must perform in a real-world, dynamically-changing environment with multiple sources of uncertainty. Finally, it serves as a case study offering insights into the integration of machine learning into the system engineering process for a large knowledge-based system development effort.     

基于专家系统的知识检索模型研究

专家知识在知识检索系统中有着强大的指导功用.本文将专家系统引入到知识检索系统中,通过设置具有不同功能及应用范围的系列专家系统,构建了基于专家系统的知识检索框架.     

A Combined System for Contactless Control of Robotic Systems by Verbal and Gesture Commands

This article considers the task of building a universal integrated intelligent system and its interface for speech and gesture-activated control of robotic systems, including means of transport and aircraft. Several foreign publications are reviewed that present combined control systems and their results. The system is integrated with a knowledge base and a data base, makes use of artificial-intelligence elements, and bears on the generality of procedures of inputting, processing, and transferring different kinds of information.     

面向专家的知识地图研究

文章首先介绍专家知识地图的定义、基本特征和分类,针对专家知识地图的基本特征、组成要素和实际应用情况,说明专家知识地图常用的构建方法,最后分别针对专家研究领域知识地图和专家社会网络知识地图进行了深入分析和举例说明。     

Methods and means of intellectual planning: Implementation of the management of process control in the construction of an integrated expert system

The problems of intellectualization in the process development of integrated expert systems on the basis of the task-oriented methodology and the AT-TECHNOLOGY instrumental software complex are considered. The experience from carrying out intellectual planning for the synthesis of architectural layouts of prototypes in integrated expert systems, a usage-based intelligent scheduler, reusable components, typical project procedures, and other components of the intellectual software environment in the AT-TECHNOLOGY complex is described.     

Formally specifying reusable knowledge model components

This paper outlines some of the problems with using predefined building blocks to specify knowledge level models of problem solving, in particular in the context of the KADS methodology. The definition of the basic building blocks in KADS, the primitive inferences, or knowledge sources, often seems to be inadequate to aid the knowledge engineer in constructing an abstract model of problem solving. We argue that the informal, verbal way in which the building blocks are defined is the cause of this problem, and propose to formalize them to make their semantics clear and to assess the consequences of various modeling decisions. We discuss choices among different formalizations, and show in detail the formalization of one class of knowledge sources.     

试论高校图书馆知识服务专家系统的建立

论文尝试建立高校图书馆知识服务专家系统,希望能为高校图书馆知识服务的开展提供一个良好的技术平台,提出了图书馆知识服务专家系统的开发步骤,并全面阐述了系统分析与设计的各个方面。     

信任视角下数据智能与专家知识的对比实证研究

[目的/意义]从信任视角对比用户对数据智能与专家知识的感知,有助于了解用户当前对这两类典型的决策信息源的信任状态及差异,进而为数据智能的深化应用、数据智能与专家知识的有效融合提供建议。[方法/过程]基于信任的经典二维度划分,即认知信任和情感信任,设计包含两对、四个潜在变量的测量量表。采用问卷调查法,获取342份有效样本,利用描述性统计和配对样本t-检验方法进行数据分析。[结果/结论]研究发现,用户对数据智能的认知信任显著高于专家知识,而对数据智能的情感信任显著低于专家知识。     

面向内容的信息服务研究

从专题门户服务、知识挖掘服务、信息内容的智能化跟踪,词表导航,知识的可视化显示,专家系统和网络计量学7个方面探讨如何深化网络信息服务。     

Supporting preprocessing and postprocessing for machine learning algorithms: a workbench for ID3

Inductive learning algorithms have been suggested as alternatives to knowledge acquisition for expert systems. However, the application of machine learning algorithms often involves a number of subsidiary tasks to be performed as well as algorithm execution itself. It is important to help the domain expert manipulate his or her data so they are suitable for a specific algorithm, and subsequently to assess the algorithm results. These activities are often called preprocessing and postprocessing. This paper discusses issues related to the application of the ID3 algorithm, an important representative of the inductive learning family. A prototype workbench which has been developed to provide an integrated approach to the application of ID3 is presented. The design rationale and the potential use of the system is justified. Finally, future directions and further enhancements of the workbench are discussed.     

论电子图书馆的智能编目专家系统

论电子图书馆的智能编目专家系统李晓红索传军ＡＢＳＴＲＡＣＴＩｎｔｅｌｉｇｅｎｔｃａｔａｌｏｇｕｉｎｇｅｘｐｅｒｔｓｙｓｔｅｍｉｓｔｏｉｎｔｅｇｒａｔｅｋｎｏｗｌｅｄｇｅａｎｄｅｘｐｅｒｉｅｎｃｅｏｆｃａｔａｌｏｇｕｉｎｇｅｘｐｅｒｔｓｉｎｔｏｃｏｍｐ...     

创新扩散驱动的领域隐性知识地图构建：以微电子领域为例

[目的 /意义]探究知识创新扩散路径下的隐性知识扩散和转移行为,据此构建蕴含专家学者隐性知识的知识地图,对推动知识共享与创新至关重要。[方法 /过程]首先从科学知识图谱与知识地图融合的角度明确创新扩散驱动的隐性知识地图构建原理,在此基础上建构隐性知识地图构建流程模型,并以微电子领域为例,围绕主题、学科、机构、地区4个维度内的创新扩散路径,衍生出隐性知识载体的内在关联,借助可视化方式构建隐性知识地图,探究专家隐性知识扩散和转移行为规律。[结果 /结论 ]提出以创新扩散为驱动的微电子领域内的隐性知识地图构建方案,追踪知识创新扩散脉络与隐性知识载体间知识流动行为,可充分满足专家定位、团队构建、专家推荐三个场景下的独特需求。     

书目情报系统适应社会发展的未来展望

书目情报系统适应社会发展的未来展望柯平Ａｂｓｔｒａｃｔ：Ｔｈｅｂｉｂｌｉｏｇｒａｐｈｉｃａｌｉｎｆｏｒｍａｔｉｏｎｓｙｓｔｅｍｋｅｅｐｓｏｎｃｈａｎｇｉｎｇｗｉｔｈｓｏｃｉａｌｄｅｖｅｌｏｐｍｅｎｔｓｉｎｗｈｉｃｈｉｔｗｉｌｌｐｌａｙａｍｏｒｅａｎｄ...     

Expert critics: operationalizing the judgement/decisionmaking literature as a theory of “bugs” and repair strategies

Humans are well-known for being adept at using their intuition and expertise in many situations. However, in some settings even human experts are susceptible to errors in judgement, and a failure to recognize the limits of knowledge. This happens often especially in semi-structured situtations, where multi-disciplinary expertise is required, or when uncertainty is a factor. At these times our natural ability to recognize and correct errors fails us, since we have faith in our reasoning. One way to deal with such problems is to have a computerized “critic” to assist in the process. This article introduces the concept of automated critics that collaborate with human experts to help improve their problem solving performance. A critic is a narrowly focused program that uses a knowledge base to help it recognize (1) what types of human error have occurred, and (2) what kinds of criticism strategies could help the user prevent or eliminate those errors. In discussing the “errors” half of this knowledge base, there is a difference between the expert's knowledge and his or her judgement. The focus in this article is more on judgement than on knowledge but both are addressed.To build automated critics it is important to understand the use and behavior of human critics. For this reason critic theory, principles and rules for design are described in this article. These are presented by showing various types of criticism encountered across a variety of generic tasks, such as medical diagnosis, coaching forecasting and authoring among many others. Thus a model of expert cognition and rules for identifying cognitive biases are presented. This rule base exploits four decades of literature on the psychology of judgement and decisionmaking as a generative theory of “bugs” in expert intuition and as a deep knowledge from which rules about buggy behavior are drawn. For the commonly recurring expert errors, specific preventive and corrective strategies are also reviewed and considerations for criticism presentation and deployment are explained. Particular attention is given to rules about when and how criticism should be offered. By consulting and attempting to operationalize the judgement and decisionmaking literature within the critiquing approach, this establishes criticism-based problem solving as a novel way to bridge the gap between the traditional domain knowledge-rich approaches of AI and the domain-independent, theory-rich approaches of decision analysis. Attention is also devoted to the obstacles to, and opportunities for, further bridging this gap.     

中国科学院文献情报系统知识创新工作评估研究与探索

阐述建立文献情报工作与服务创新评估机制的重要性。重点论述建立中国科学院文献情报系统知识创新试评价制度的目的、目标、规划和实践。详细介绍科技文献信息知识创新工作与服务评价方案、指标体系的研制以及年度评价实施情况,并根据评估研究和实践提出可借鉴的经验和发展建议。     

数据网络中中文名称规范档的建设与发展

[目的/意义]名称规范档在书目数据库中对书目记录的检索点进行规范化校验,通过实现标目的一致性,达到检索效率提升、目录汇集的目的。分析国外名称规范档的最新研究进展及实践,以期为中文名称规范档的发展研究提供借鉴。[方法/过程]通过对当前中文名称规范档建设存在的问题进行客观分析,结合国外名称规范档的研究进展及实践,提出中文名称规范档的建设发展方向。[结果/结论]当前中文名称规范档的建设存在着数据规模小、数据完全性差、数据共享性低问题,从国外名称规范档的发展看出,其不再局限于图书馆内部建设,开始向合作共建共享发展,规范数据不再面向OPAC系统,向开放互联发展。因此中文名称规范档的建设可从共建共享、构建新模型与规则、提升质量方面着手,发挥中文名称规范档在网络环境下的规范控制作用。     

Mutual implications and granularity

This paper illustrates a technique for discovering mutual implications among hierarchically structured data. Such a technique may be applied to both knowledge and data bases. If the hierarchical structure makes it possible to define granularity levels, mutual implications can be evaluated at any level. Results can be quantitative (i.e. a degree in the range [0, 1]) or qualitative (i.e. a label taken from a user-defined set). If the ground data do not represent a mapping among individuals, i.e. the level of information granularity is not the highest, a local approximation based on T-Norms can be used. The process of implication discovery allows one to derive inference rules for expert systems and to detect default values. In addition, it might be successfully used by sophisticated machine learning algorithms.     

基于本体的专利摘要知识抽取*

采用知识工程的方法,对“新能源汽车”中文专利摘要进行研究分析,提出了一个基于本体的中文专利摘要抽取模型。通过构建相应的本体、收集相关的词表、撰写相应的规则,并利用这些规则对专利摘要进行知识抽取结果,抽取结果辅助完成专利知识库的自动构建。即就如何组织非结构化信息以及如何自动构建知识库的进行尝试,验证了基于本体对专利摘要进行知识抽取的可行性。