Semantic model for knowledge representation in e-business

Semantic knowledge representation is the key for the development of present intelligent systems. Furthermore, the Semantic Web provide a formal representation and knowledge-driven set of technologies to enable automation of business processes. Despite the new trends on business process automation based on semantic technologies and Web Services, a number of business processes still require human intervention. In this paper we address the problem of ontology-based process representation based on expert’s knowledge, considering both tasks executed by means of web services and tasks executed by persons. In this way, fully-automated and semi-automated processes (guided by a person) could be represented and executed. The proposed model is based on the set of situations that can be identified by an expert in a given process and the actions required in each situation. For validating our approach, a sales supporting system based on the proposed architecture has been developed. The proof-of concept system has been running for a remarkably time, supporting the sales process for non-expert sellers.     

Expert systems applied to problems in geographic information systems: Introduction, review and prospects

This paper critically reviews current expert system developments relevant to geographic information systems, and identifies several research topics for application of expert system technology in geographic information systems. We have identified four major problem domains of geographic information systems in which expert system technology has been applied—automated map design, terrain/feature extraction, database management/user interface, and geographic decision support systems. Efforts in each problem domain are critically reviewed. Considering the accomplishments and shortcomings of efforts to date, we identify areas likely to gain importance in this field. Our view of these prospects is moderated by constraints of current technology and a realistic view of current efforts. Future research will place more emphasis on formal representation of both knowledge and uncertainty. Another future research area will be the development of advanced tools for geographic knowledge acquisition. Finally, better methods for working with large-scale geographic databases will be needed.     

应急资源本体模型研究*

针对应急资源在知识表示与理解中存在的语义冲突问题,将本体技术引入领域知识表示,提出一种通用的应急资源概念模型。以SUMO为上位本体,从应急资源的管理和应急资源的配置使用两个方面构建应急资源本体模型 (emergency resource ontology model,EROM),为应急管理和应急资源共享提供语义层次的统一表达和理解。     

An integrated case-based reasoning approach for intelligent help desk fault management

As modern business functions become more complex and knowledge-intensive, with increasing demands for quality services, there is an emerging trend for organisations to develop and deploy intelligent knowledge-based systems for mission-critical operations. Some of the challenges in successfully implementing this breed of systems depend on how well the intelligent system is integrated with conventional existing information systems and workflow, and the quality of the intelligent system itself. Developing quality expert systems lies in the effective modelling of cognitive processes of human experts and representation of various forms of related knowledge in a domain. An integrated intelligent system called the Intelligent Help Desk Facilitator (IHDF), has been developed for computer and network fault management. The system, which comprises various modules including an expert system, is successfully deployed in a problem response help desk environment of a local bank. This paper describes a cognitive-driven approach to the development of the expert system based on a hybrid knowledge representation and reasoning strategy. The approach incorporates a hybrid case-based reasoning (CBR) framework of techniques which include case memory organisation structures (discrimination networks and shared-featured networks), case indexing and retrieval schemes (fuzzy character-matching, nearest-neighbour similarity matching and knowledge-guided indexing); and an interactive and incremental style of reasoning. The paper discusses the design and implementation of the expert system component of IHDF and illustrates the appropriateness of the hybrid architecture for problem resolution and diagnostic types of applications.     

青光眼医疗智能诊断系统的设计与实施

论述产生式知识表示、语义树知识表示在基于三大类青光眼诊断专家系统中的应用,并将关系数据库技术引入专家系统,对检查问诊数据进行存储.针对青光眼诊断过程层次性和复杂性的特点,综合采用深度优先语义遍历,正向启发式推理策略,实现了行之有效的推理机制,获得了较好的推理效果.     

NUREST:一个实时专家系统开发工具

对实时专家系统的特点作了概要论述,将专家系统技术和实时控制技术相结合,设计并实现了应用于实时问题求解的实时专家系统开发工具NUREST。主要讨论了它的知识表示、实时控制机制、推理机制以及实现技术,并给出了开发的炼钢控制实时专家系统实例。     

An approach to expert control of interactive software systems

Expert problem-solving strategies in many domains require the use of detailed mathematical techniques coupled with experiential knowledge about how and when to use the appropriate techniques. In many of these domains, such techniques are made available to experts in large software packages. In attempting to build expert systems for these domains, we wish to make use of these packages, and are therefore faced with an important problem: how to integrate the existing software, and knowledge about its use, into a practical expert system. The expert knowledge is used, in dynamic selection and interpretation of appropriate programs and parameters, to reach a successful goal in the problem solving. We describe the framework of a hybrid expert system for representing problem-solving knowledge in these domains. This hybrid system may be characterized as consisting of a production system and mathematical methods. The software package is reorganized as necessary to map it into the mathematical-method representation of a hybrid system. This approach has evolved out of an effort to build an expert system for performing well-log analysis, ELAS (expert log analysis system).     

REX: Robotics expert systems building tool

REX, an expert systems development shell for robotics applications, is presented in the paper. The shell is intended for building expert systems in various domains of robotics, including design, planning, control, fault-detection, and navigation. REX's knowledge and data representation techniques include several standard techniques, like rules, frames, parameters, and variables, as well as certain techniques which are not commonly used by other expert systems building tools. These specific techniques include sensor data, status data, models and algorithms. The REX inference engine provides a means for reasoning with all of these knowledge and data types. The inference engine features both off-line and on-line modes of operation. REX has powerful interfaces for communicating both with the user and with other software modules in a complex application. Certain learning techniques are built into the shell. An example of applying REX for building an expert system in the domain of robot control is also presented. Finally, a discussion is provided on the relation between REX and second-generation expert systems.     

PGSW-OS: a novel approach for resource management in a semantic web operating system based on a P2P grid architecture

A web operating system is an operating system that users can access from any hardware at any location. A peer-to-peer (P2P) grid uses P2P communication for resource management and communication between nodes in a grid and manages resources locally in each cluster, and this provides a proper architecture for a web operating system. Use of semantic technology in web operating systems is an emerging field that improves the management and discovery of resources and services. In this paper, we propose PGSW-OS (P2P grid semantic Web OS), a model based on a P2P grid architecture and semantic technology to improve resource management in a web operating system through resource discovery with the aid of semantic features. Our approach integrates distributed hash tables (DHTs) and semantic overlay networks to enable semantic-based resource management by advertising resources in the DHT based upon their annotations to enable semantic-based resource matchmaking. Our model includes ontologies and virtual organizations. Our technique decreases the computational complexity of searching in a web operating system environment. We perform a simulation study using the Gridsim simulator, and our experiments show that our model provides enhanced utilization of resources, better search expressiveness, scalability, and precision.     

Knowledge acquisition for fuzzy expert systems

Expert systems have been successfully applied to a wide variety of application domains. to achieve better performance, researchers have tried to employ fuzzy logic to the development of expert systems. However, as fuzzy rules and membership functions are difficult to define, most of the existing tools and environments for expert systems do not support fuzzy representation and reasoning. Thus, it is time-consuming to develop fuzzy expert systems. In this article we propose a new approach to elicit expertise and to generate knowledge bases for fuzzy expert systems. A knowledge acquisition system based upon the approach is also presented, which can help knowledge engineers to create, adjust, debug, and execute fuzzy expert systems. Some control techniques are employed in the knowledge acquisition system so that the concepts of fuzzy logic could be directly applied to conventional expert system shells; moreover, a graphic user interface is provided to facilitate the adjustment of membership functions and the display of outputs. the knowledge acquisition system has been integrated with a popular expert system shell, CLIPS, to offer a complete development environment for knowledge engineers. With the help of this environment, the development of fuzzy expert systems becomes much more convenient and efficient. © 1995 John Wiley & Sons, Inc.     

Brussels revisited: The European conflicts guide

In this paper, we examine the soundness of Capper & Susskind's recommended legal expert system development methodology in the areas of knowledge acquisition and knowledge representation. Legal expert systems have not yet had the impact in the United Kingdom that might be expected. We argue that this is partly the result of developers paying insufficient attention to the ‘third estate’: user interfaces. We make suggestions about both the look and feel of legal expert systems, and the facilities that such systems should offer. Lastly, we claim that we have developed an exploratory expert system encapsulating the Brussels Convention 1968 which can contribute to the development of a useful computer‐based guide to an important legal domain.     

专家领域本体建模及语义信息服务研究

目前各省市各部门分别拥有各自专用的专家信息系统,分别管理所在地区和所属领域的专家信息,其形式各异且专家信息分布异构.针对实际应用中共享专家信息困难,基于关键字查询信息效率不高等问题,提出基于语义的专家信息系统解决方案.采用5W1H分析法归纳领域本体中概念和关系,建立基于5W1H的专家本体概念模型并生成专家领域本体,实现了专家语义信息统一建模.构建系统的四层体系结构,研究语义推理规则的定义方法,设计了基于语义的规则推理算法和基于SPAR-QL的语义信息查询算法,实现了系统基于语义的信息查询和推理等功能.实验表明,基于语义的专家信息查询在查全率、查准率优于基于关键字的查询.     

ON KNOWLEDGE REPRESENTATION FOR INFERENCES IN CAST METHOD BANKS

This article explains why aspects of knowledge representation must be considered in the context of computer aided systems theory (CAST). CAST method banks support human experts during the process of problem solving. They should be understood as decision support systems, as assistants of their human expert users. One key to making this approach work is the communication between the expert and the system. The assistant should provide systematical and goal-directive information about the current problem state for the human expert. Another, even more important requirement is the assistant's knowledge about all available methods at a certain problem-solving state and their expected impact on the further problem-solving process. Knowledge representation denotes how the problem domain is represented within the support system and how it is used. We investigate different forms of knowledge representations and summarize criteria for the applicability of different forms of knowledge representations in CAST systems.     

基于面向服务架构的疾控中心人力资源管理系统设计与实现研究

作为疾控中心稳定有序发展的根本,人力资源的重要作用不容忽视,因此疾控中心需构建专业队伍,以积极预防控制各种类型疾病,确保人们生命健康.对此本文基于面向服务架构设计了疾控中心人力资源管理系统.系统实现了疾控中心人力资源管理多元化需求,提供多样接口拓展全新功能,可与其他管理系统有机结合,以此优化完善人力资源管理.并且通过系...     

Computer-assisted localization of nervous system injuries

Expert systems to assist in neurological diagnosis require a representation of anatomical relationships. In order to test one representational method, a prototype expert system was developed. It accepts patient signs of neurological dysfunction and identifies the site of nervous system injury. The system's knowledge base is contained in a semantic network which represents nervous system anatomy and the physical signs of injuries. When provided with an individual's physical signs, the network is searched by a simple algorithm; the anatomical locations which best explain the physical signs are the system's output. Medical expert systems which require anatomical reasoning can use a direct representation of spatial relationships to avoid the difficulties of encoding clinical associations in the form of If-Then rules.     

Sentence similarity based on semantic nets and corpus statistics

Sentence similarity measures play an increasingly important role in text-related research and applications in areas such as text mining, Web page retrieval, and dialogue systems. Existing methods for computing sentence similarity have been adopted from approaches used for long text documents. These methods process sentences in a very high-dimensional space and are consequently inefficient, require human input, and are not adaptable to some application domains. This paper focuses directly on computing the similarity between very short texts of sentence length. It presents an algorithm that takes account of semantic information and word order information implied in the sentences. The semantic similarity of two sentences is calculated using information from a structured lexical database and from corpus statistics. The use of a lexical database enables our method to model human common sense knowledge and the incorporation of corpus statistics allows our method to be adaptable to different domains. The proposed method can be used in a variety of applications that involve text knowledge representation and discovery. Experiments on two sets of selected sentence pairs demonstrate that the proposed method provides a similarity measure that shows a significant correlation to human intuition.     

ISTAR — a tool for creative design of knowledge bases

This paper gives a comprehensive explanation of the Istar knowledge representation software tool. Not only does it describe the features and facilities found in Istar, but it discusses why they are as they are.
Istar is one of a new generation of knowledge representation tools, aimed at ill-structured domains of knowledge. While it can be used in traditional KBS projects, in which pieces of knowledge from a domain expert are assembled to form a working knowledge base, it is designed for situations in which there is a large element of creative design: knowledge refinement and generation resulting from the knowledge representation process.
The knowledge representation 'language' is purely graphical; the knowledge engineer 'draws' knowledge on an easel as a box and arrows diagram. Behind this diagram is the knowledge base itself, in the form of integrated inference nets, Bayesian nets and semantic nets. This paper discusses the reasons for these design choices and, briefly, some of the issues faced in development of Istar.     

An Ontology-Based Approach for Semantic Conflict Resolution in Database Integration

An important task in database integration is to resolve data conflicts, on both schema-level and semantic-level. Especially difficult the latter is. Some existing ontology-based approaches have been criticized for their lack of domain generality and semantic richness. With the aim to overcome these limitations, this paper introduces a systematic approach for detecting and resolving various semantic conflicts in heterogeneous databases, which includes two important parts： a semantic conflict representation model based on our classification framework of semantic conflicts, and a methodology for detecting and resolving semantic conflicts based on this model. The system has been developed, experimental evaluations on which indicate that this approach can resolve much of the semantic conflicts effectively, and keep independent of domains and integration patterns.