University Knowledge Management Tool for Academic Research Activity Evaluation

The implementation of an efficient university knowledge management system involves the de-velopment of several software tools that assist the decision making process for the three main activities of a university: teaching, research, and management. Artificial intelligence provides a variety of techniques that can be used by such tools: machine learning, data mining, text mining, knowledge based systems, expert systems, case-based reasoning, decision support systems, intelligent agents etc. In this paper it is proposed a generic structure of a university knowledge management system, and it is presented an expert system, ACDI_UPG, developed for academic research activity evaluation, that can be used as a decision support tool by the university knowledge management system for planning future research activities according to the main objectives of the university and of the national / international academic research funding organizations.University Knowledge Management, Research Activity Evaluation, Artificial Intelligence, Expert Systems, Decision Support System

Creating New Pathways to Justice Using Simple Artificial Intelligence and Online Dispute Resolution

Access to justice in can be improved significantly through implementation of simple artificial intelligence (AI) based expert systems deployed within a broader online dispute resolution (ODR) framework. Simple expert systems can bridge the ‘implementation gap’ that continues to impede the adoption of AI in the justice domain. This gap can be narrowed further through the design of multi-disciplinary expert systems that address user needs through simple, non-legalistic user interfaces. This article provides a non-technical conceptual description of an expert system designed to enhance access to justice for non-experts. The system’s knowledge base would be populated with expert knowledge from the justice and dispute resolution domains. A conditional logic rule-based system forms the basis of the inference engine located between the knowledge base and a questionnaire-based user interface. The expert system’s functions include problem diagnosis, delivery of customized information, self-help support, triage and streaming into subsequent ODR processes. Its usability is optimized through the engagement of human computer interaction (HCI) and effective computing techniques that engage the social and emotional sides of technology. The conceptual descriptions offered in this article draw support from empirical observations of an innovative project aimed at creating an expert system for an ODR-enabled civil justice tribunal

Creating New Pathways to Justice Using Simple Artificial Intelligence and Online Dispute Resolution

Access to justice in can be improved significantly through implementation of simple artificial intelligence (AI) based expert systems deployed within a broader online dispute resolution (ODR) framework. Simple expert systems can bridge the ‘implementation gap’ that continues to impede the adoption of AI in the justice domain. This gap can be narrowed further through the design of multi-disciplinary expert systems that address user needs through simple, non-legalistic user interfaces. This article provides a non-technical conceptual description of an expert system designed to enhance access to justice for non-experts. The system’s knowledge base would be populated with expert knowledge from the justice and dispute resolution domains. A conditional logic rule-based system forms the basis of the inference engine located between the knowledge base and a questionnaire-based user interface. The expert system’s functions include problem diagnosis, delivery of customized information, self-help support, triage and streaming into subsequent ODR processes. Its usability is optimized through the engagement of human computer interaction (HCI) and effective computing techniques that engage the social and emotional sides of technology. The conceptual descriptions offered in this article draw support from empirical observations of an innovative project aimed at creating an expert system for an ODR-enabled civil justice tribunal

Intelligent approaches to performance support

Electronic performance support systems provide an important method of meeting on‐demand educational and training requirements. They also provide efficient and effective ways of enabling the knowledge and expertise within an organization to be shared. This paper discusses the design of a distributed electronic performance support system and the ways in which ‘intelligent agents’ based on expert systems and neural networks can be used to locate and share distributed expertise. A case study illustrating our approach to the implementation and use of intelligent agents is presented

Tools and technologies for expert systems: A human factors perspective

It is widely recognized that technologies based on artificial intelligence (AI), especially expert systems, can make significant contributions to the productivity and effectiveness of operations of information and knowledge intensive organizations such as NASA. At the same time, these being relatively new technologies, there is the problem of transfering technology to key personnel of such organizations. The problems of examining the potential of expert systems and of technology transfer is addressed in the context of human factors applications. One of the topics of interest was the investigation of the potential use of expert system building tools, particularly NEXPERT as a technology transfer medium. Two basic conclusions were reached in this regard. First, NEXPERT is an excellent tool for rapid prototyping of experimental expert systems, but not ideal as a delivery vehicle. Therefore, it is not a substitute for general purpose system implementation languages such a LISP or C. This assertion probably holds for nearly all such tools on the market today. Second, an effective technology transfer mechanism is to formulate and implement expert systems for problems which members of the organization in question can relate to. For this purpose, the LIghting EnGineering Expert (LIEGE) was implemented using NEXPERT as the tool for technology transfer and to illustrate the value of expert systems to the activities of the Man-System Division

SYSTEMATIC OF EXPERT SYSTEM BASE ON SOFTWARE AND CALCULATION METHOD

The expert system is a system that seeks to adopt human knowledge into technology, so that technology can solve problems as is usually done by experts. A good expert system is designed to solve a particular problem by imitating the work of the experts. With expert systems, the layman can solve quite complicated problems, because in fact the problem can only be solved with the help of experts. For experts, the expert system will also assist its activities as a highly experienced assistant. Currently there are many studies that raise cases about expert systems. This study aims to create systematic on expert systems based on a collection of expert system cases and classify them based on the tools used, implementation types and frequently used methods

DATABASE ACCESS REQUIREMENTS OF KNOWLEDGE-BASED SYSTEMS

Knowledge bases constitute the core of those Artificial Intelligence programs which have come to be known as Expert Systems. An examination of the most dominant knowledge representation schemes used in these systems reveals that a knowledge base can, and possibly should, be described at several levels using different schemes, including those traditionally used in operational databases. This chapter provides evidence that solutions to the organization and access problem for very large knowledge bases require the employment of appropriate database management methods, at least for the lowest level of description -- the facts or data. We identify the database access requirements of knowledge-based or expert systems and then present four general architectural strategies for the design of expert systems that interact with databases, together with specific recommendations for their suitability in particular situations. An implementation of the most advanced and ambitious of these strategies is then discussed in some detail.Information Systems Working Papers Serie

Clips as a knowledge based language

CLIPS is a language for writing expert systems applications on a personal or small computer. Here, the CLIPS programming language is described and compared to three other artificial intelligence (AI) languages (LISP, Prolog, and OPS5) with regard to the processing they provide for the implementation of a knowledge based system (KBS). A discussion is given on how CLIPS would be used in a control system

Application of Knowledge-based Tools in Environmental Decision Support Systems

Decision support system often requires the combined knowledge of multiple domains. A knowledge-based approach is proposed to include not only the process modelling knowledge but also the descriptive knowledge in the integration. Descriptive knowledge such as survey statistics and expert opinions forms the core of a study on the uncertainty of the combined knowledge. It was found that the use of expert systems, neural network and belief causal network assist greatly in the implementation of these concepts. Examples are drawn from the combination of scientific and economic knowledge to solve some acid rain problems.decision support system; knowledge-based system; expert system; causal network

Towards a framework for threaded inference in rule-based systems

Abstract: Information and communication technologies have shown a significant advance and fast pace in their performance and pervasiveness. Knowledge has become a significant asset for organizations, which need to deal with large amounts of data and information to produce valuable knowledge. Dealing with knowledge is turning the axis for organizations in the new economy. One of the choices to gather the goal of knowledge managing is the use of rule-based systems. This kind of approach is the new chance for expert-systems’ technology. Modern languages and cheap computing allow the implementation of concurrent systems for dealing huge volumes of information in organizations. The present work is aimed at proposing the use of contemporary programming elements, as easy to exploit threading, when implementing rule-based treatment over huge data volumes. Keywords: inference, thread, rule, expert, knowledge, framework