Mining for knowledge in databases: The INLEN architecture,initial implementation and first results

The architecture of an intelligent multistrategy assistant for knowledge discovery from facts, INLEN, is described and illustrated by an exploratory application. INLEN integrates a database, a knowledge base, and machine learning methods within a uniform user-oriented framework. A variety of machine learning programs are incorporated into the system to serve as high-levelknowledge generation operators (KGOs). These operators can generate diverse kinds of knowledge about the properties and regularities existing in the data. For example, they can hypothesize general rules from facts, optimize the rules according to problem-dependent criteria, determine differences and similarities among groups of facts, propose new variables, create conceptual classifications, determine equations governing numeric variables and the conditions under which the equations apply, deriving statistical properties and using them for qualitative evaluations, etc. The initial implementation of the system, INLEN 1b, is described, and its performance is illustrated by applying it to a database of scientific publications.     

基于改进的BP网络的语法分析系统设计

针对汉语语法分析问题提出了一种基于改进的BP网络的语法分析专家系统的设计方案。其核心是构造存储和管理文法知识的知识库及具有语言专家智能行为和语法分析能力的推理机。本系统中知识库采用产生式规则的知识表达方式，并将知识二元化存储在神经网络中；推理机采用神经网络进行推理。最后给出了系统的运行实例，说明该系统的有效性。     

The complementary roles of expert systems and database management systems in a design for manufacture environment

Effective product design that satisfies functional requirements and can be manufactured easily requires vast amounts of knowledge on the part of the design engineer. This paper focuses on the complementary roles of expert systems and database management systems as they relate to the Intelligent Design System (IDS) in a Design for Manufacture (DFM) environment. Each technology complements the other in its strengths and abilities. The database management system provides during the design process. The expert system provides a reasoning mechanism for identifying manufacturing violations and generating meaningful recommendations. These components work cooperatively with a CAD interface to form a unified, intelligent design environment.An information flow analysis of the Intelligent Design System resulted in the development of three distinct classifications of information within the database: CAD data, a design catalog, and a knowledge base. The CAD data tables employ an, object oriented approach to store specific information about the physical contains cost, weight, and strength characteristics of the standard parts and fasteners used within the system. The knowledge base contains rules and heuristics concerning design and manufacturing methodologies.The placement of the expert system rules in the database represents an innovation. As a result, the expansion and updating of the materials, fasteners, standard parts, or manufacturing processes used by the Intelligent Design System is facilitated without increased due to the efficient management of the knowledge base by the database management system. This allows the designer to modify the knowledge and help the system to learn without the need for a knowledge engineer.     

KNOWLEDGEABLE LEARNING USING MOBAL: A MEDICAL CASE STUDY

Building up a knowledge base is a complex task in which theoretical knowledge needs to be integrated with practical experience. This integration can be supported by a system that can manage linking between rules, representing experts or textbook or theoretical knowledge and facts (or data), representing cases from practice. Conflicts between rules and real-world cases can have diverse causes. Case data can be noisy or inconsistent or both. We use rules to filter cases and confine noise or inconsistency. However, rules can be overly general and can classify more cases than intended. Then machine learning can be used to find additional restrictions for the rules. If, however, no significant similarities can be determined between the misclassified cases, we seek additional expert input to support effective implementation of learning tools. Using a case subset, we capture expert input and formulate a set of “enriched” cases. We then use the enriched cases to learn additional rules and to introduce practical features to validate and refine the original rule base. In this paper, we discuss the role of machine learning as a vehicle for supporting     

Designing and supporting HMO,an integrated hardware microcode optimizer

This paper discusses an algorithm for optimizing the density and parallelism of microcoded routines in microprogrammable machines. Besides presenting the algorithm itself, this research also analyzes the algorithm's uses, design integration problems, architectural requirements and adaptability to conventional machine characteristics. Even though the paper proposes a hardware implementation of the algorithm, the algorithm is viewed as an integral part of the entire microcode generation and usage process, from initial high-level input into a software microcode compiler down to machine-level execution of the resultant microcode on the host machine. It is believed that, by removing much of the traditionally time-consuming and machine-dependent microcode optimization from the software portion of this process, the algorithm can improve the overall process.     

A unification-based approach for knowledge base verification

Abstract: Knowledge base verification, a part of the validation process in expert system development, includes checking the knowledge base for completeness and consistency to guard against a variety of errors that can arise during the process of transferring expertise from a human expert to a computer system. Regardless of how an expert system is developed, its developers can profit from a systematic check of the knowledge base without gathering extensive data for test runs, even before the full reasoning mechanism is functioning. Until recently knowledge base verification has been largely ignored, which has led to expert systems with knowledge base errors and no safety factors for correctness. We propose a unification-based approach for verification of a knowledge base represented in the form of production rules and facts. This approach can determine conflicting, redundant, subsumed and circular rules; redundant if-conditions in rules; dead-end rules; and cycles and contradiction in rules.     

EMERGE-A Data-Driven Medical Decision Making Aid

EMERGE is an expert system designed as a medical decision making aid. It is machine-independent, and is implemented in standard Pascal. It has modest memory requirements, and can operate on a microcomputer. EMERGE is rule-based, and its initial application is the analysis of chest pain in the emergency room. The knowledge base is maintained separately from the consultation program. Thus the application area can be changed without any modification to the software. This paper describes the control structures and rule searching procedures used in EMERGE.     

基于关联规则数据挖掘技术在教学管理中的应用

数据挖掘技术是一种新的信息处理技术。其目的是从海量数据中抽取潜在的,有价值的数据规律或数据模型。通过数据挖掘技术对高校教学数据的分析处理,能够形成真正有价值的知识,向决策者提供信息支持,有利于推动学校教学改革和建设的全面发展。本文主要针对现行高校实际运作的学分选课数据库系统,以关联规则挖掘为例,提出简单而可行的数据挖掘应用实施办法。     

A Strategy of Dynamic Reasoning in Knowledge-Based System with Fuzzy Production Rules

Fuzzy production rules have been successfully applied to represent uncertainty in a knowledge-based system. The knowledge organized as a knowledge base is static. On the other hand, a real system such as the stock market is dynamic in nature. Therefore we need a strategy to reflect the dynamic nature of a system when we make reasoning with a knowledge-based system.This paper proposes a strategy of dynamic reasoning that can be used to takes account the dynamic behavior of decision-making with the knowledge-based system consisted of fuzzy rules. A degree of match (DM) between actual input information and antecedent of a rule is represented by a value in interval [0, 1]. Weights of relative importance of attributes in a rule are obtained by the AHP (Analytic Hierarchy Process) method. Then these weights are applied as exponents for the DM, and the DMs in a rule are combined, with the Min operator, into a single DM for the rule. In this way, the importance of attributes of a rule, which can be changed from time to time, can be reflected to reasoning in knowledge-based system with fuzzy rules.With the proposed reasoning procedure, a decision maker can take his judgment on the given decision environment into a static knowledge base with fuzzy rules when he makes decision with the knowledge base. This procedure can be automated as a pre-processing system for fuzzy expert systems. Thereby the quality of decisions could be enhanced.     

一个面向样本利用的智能系统的实现

本文实现了一个面向样本利用的智能系统ＩＳＳＵ,它能够完成样本的输入,具有样本学习的能力,并且能将样本知识自动转化为产生式规则,将产生式规则自动转化为框架知识,在此基础上还实现了一个基于框架的推理机。对ＩＳＳＵ的系统结构和实现技术进行了论述,并介绍了一个应用系统。     

Finite element mesh design expert system

The paper presents a consultative rule-based expert system for finite element mesh design. The aim of the expert system presented is to propose the appropriate type of the finite elements and determine the resolution values for the finite element mesh to be used for the analysis. The extensive knowledge base, comprising about 1900 rules, was built mainly by the use of machine learning (ML) techniques. Several examples will confirm that an expert system shell written in Prolog enables efficient use of the knowledge base and adequate communication between the system and the user. The system has the ability to explain the inference process. Thus, it can also be used as a teaching tool for inexperienced users—students. The results of the experimental use of the system are encouraging and can be used as guidelines for further developments and improvements of the system.     

基于规则库的变压器故障监测专家系统

针对变压器在线监测中缺乏状态方程的问题,设计了一种基于规则库的变压器故障实时监测的专家系统。首先以规则形式对专家知识进行编码。其次为了提高系统运行速度,方便规则的存储和管理,采用转化方案对规则进行了规范化处理,将规则以统一的形式存储在知识库中。最后提出了一种自动消除冗余规则的算法,得到所需的最小规则库。实验表明,该设计很好地模拟了人类专家对变压器故障的推理过程。     

基于知识库的客户网购意向预测系统

电子商务网站所产生的海量客户网购行为数据中蕴含着丰富的反映客户网购行为规律的知识。这些知识是进行客户网购意向预测以及在此基础上进一步进行商品推荐的重要依据。基于Hadoop框架构建了“客户购买意向预测系统”,实现了利用隐含在交易数据中的知识对正在浏览中的电商客户的购买意向预测。在基于知识图谱技术构建网购客户购买行为知识库的基础上,利用FP-Growth算法和数据统计方法实现了以增量方式从购买者的交易数据中获取反映用户购买规律的知识,并将取得的知识融合到知识库中。系统能够利用存储于知识库中的知识在客户进行网上购物的过程中对其购买意向进行分析和预测,从而达到提高电子商务平台的运营效率,改善客户购物体验的目的。     

军事领域本体构建研究

在仿真系统的研究过程中,面临军事领域知识获取及不同应用之间的互操作等问题.这些难题的背后实际是技术人员和军事人员之间理解一致性和机器之间理解一致性的问题.本体是关于事物本质的模型,已被广泛应用于知识分类、表达、共享及重用等方面.首先,讨论了本体的概念并给出了领域本体构建的一套通用原则和方法.然后详细分析了军事领域本体所包含的各方面知识元素,包括作战单元类、单元之间的关系、交战行为、交战规则、武器装备、作战计划等,并分别给出了它们的简单表示结构.最后概要讨论了多个本体合并时的本体检验问题.标准化的军事知识表示结构可以为技术人员和军事人员之间的交流提供统一的认识和参照,为机器之间的互操作提供一种"语言",从而消除理解上的冲突和混乱,为作战仿真系统的开发扫清了道路.     

MUSS—a portable operating system

This paper describes a technique for producing a machine-independent operating system with a high level of performance. The technique is based on the definition of a hypothetical ideal machine, which acts as the target computer for the operating system. The characteristics of this ideal machine are described in detail.     

A development environment for horizontal microcode

A development environment for horizontal microcode is described that uses percolation scheduling-a transformational system for parallelism extraction-and an interactive profiling system to give the user control over the microcode compaction process while reducing the burdensome details of architecture, correctness preservation, and synchronization. Through a graphical interface, the user suggests what can be executed in parallel, while the system performs the actual changes using semantics-preserving transformations. If a request cannot be satisfied, the system reports the problem causing the failure. The user can then help eliminate the problem by supplying guidance or information not explicit in the code     

基于Java的通用不精确正向推理机的设计与实现

设计和开发了一个在网络上具有良好使用性能的通用不精确正向推理机.采用了Java语言和EJB技术来实现通用不精确正向推理机,并以中间件的形式实现了对知识库的操作.文中介绍了其设计思想,同时介绍了不精确正向推理机的实现方法.结果表明实际使用效果良好.同时,该推理机具有能在网络上共享、通用和不精确推理等特性,实现方便,可以基于它来构建功能更加强大的专家系统.     

Formal reasoning in intelligent database systems

Expert database systems were proposed to solve the difficulties encountered in traditional database systems. Prolog provides a fast prototyping tool for building such database systems. However, an intelligent database system implemented in Prolog faces a major restriction that only Horn rules are allowed in the knowledge base. We propose a theorem prover which can make inference for non-Horn intelligent database systems. Conclusions can be deduced from the facts and rules stored in a knowledge base. For a knowledge base with a finite domain, the prover can provide correct answers to queries, derive logical consequences of the database, and provide help in detecting inconsistencies or locating bugs in the database. The theorem prover is efficient in deriving conclusions from large knowledge bases which might swamp most of the other deductive systems. The theorem prover is also useful in solving heuristically the satisfiability problem related to a database with an infinite domain. A truth maintenance mechanism is provided to help eliminate repetitious work for the same goals.Supported by National Science Council under grant NSC 81-0408-E-110-9.     

几何效应的可拓知识表示研究

科学效应中蕴含庞大的科学知识,是面向功能矛盾问题求解的重要基础。为了建立科学效应的可拓知识库,实现面向功能问题的可拓智能设计,提出了一种以几何效应为例的面向实际应用的可拓知识表示方法,利用该方法对实际问题中几何效应的输入与输出关系所蕴含的可拓知识进行形式化表示。首先根据几何效应,建立基元模型;根据领域知识和可拓学中的相关规则,建立基元间的相关关系;根据主动变换、传导变换知识和基元的发散规则,对相关网中某基元实施主动变换;再根据可拓变换的蕴含系和传导变换规则,得到一系列的传导变换,进而建立可拓知识表达式,实现输入与输出的转换关系的表达;最后以双曲面搅拌器设计为例进一步拓展相应的可拓知识以解决领域问题。本研究可以使设计人员更加全面地理解几何效应实现的机理,以便更准确地选择应用几何效应解决实际问题,也为其他类型科学效应的可拓知识表示研究打下良好基础。     

Intelligent Fril/SQL interrogator

The intelligent Fril/SQL interrogator is an object‐oriented and knowledge‐based support query system, which is implemented by the set of logic objects linking one another. These logic objects integrate SQL query, support logic programming language—Fril and Fril query together by processing them in sequence in slots of each logic object. This approach therefore takes advantage of both object‐oriented system and a logic programming‐based system. Fuzzy logic data mining and a machine learning tool kit built in the intelligent interrogator can automatically provide a knowledge base or rules to assist a human to analyze huge data sets or create intelligent controllers. Alternatively, users can write or edit the knowledge base or rules according to their requirements, so that the intelligent interrogator is also a support logic programming environment where users can write and run various Fril programs through these logic objects. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 279–302, 2007.