A novel approach to interactively acquire knowledge about new objects in a logic environment is presented. When the user supplies an unknown fact containing unknown objects (constants), the system will ask interesting membership and existential queries about the objects. The answers to these questions allow the system to update its knowledge base. Two basic strategies are implemented: one that ...

Conceptual Information Systems unfold the conceptual structure of data stored in relational databases. In the design phase of the system, conceptual hierarchies have to be created which describe diier-ent aspects of the data. In this paper, we describe two principal ways of designing such conceptual hierarchies, data driven design and theory driven design, and discuss advantages and drawbacks. ...

Natural language generation (nlg) systems are computer software systems that produce texts in English and other human languages, often from non-linguistic input data. nlg systems, like most ai systems, need substantial amounts of knowledge. However, our experience in two nlg projects suggests that it is difficult to acquire correct knowledge for nlg systems; indeed, every knowledge acquisition ...

Knowledge management has recently become the focus of public attention in business and engineering. Because knowledge acquisition is situated in the upstream of knowledge management, capturing knowledge is an important step for enterprises to achieve successful knowledge management. We focus on how engineers solve their design problems under given design contexts and propose a novel model and m...

One of the unresolved problems faced in the construction of intelligent tutoring systems is the acquisition of background knowledge, either for the specification of the teaching strategy, or for the construction of the student model, identifying the deviations of students’ behavior. In this paper, we argue that the use of sequential pattern mining and constraint relaxations can be used to autom...

Membership queries extended with the meta query concept is proposed as a method to acquire complex classification rules. Furthermore , relevent concept classes, where a small number of queries is sufficient, are characterized. In this paper we advocate and present the benefits of the use of queries in order to learn a target concept efficiently. Thus providing the foundations for automating the...

This paper presents our approach and a fully implemented system for incrementally building complex adaptation functions for casebased reasoning (CBR) systems. Building a CBR system still remains a difficult task due to the difficulties of developing suitable retrieval and adaptation mechanisms for a given application. To address these difficulties, we extended the basic Ripple Down Rules framew...

Explanation-Based Learning (EBL) is a widely-used technique for acquiring searchcontrol knowledge. Recently, Prieditis, van Harmelen, and Bundy pointed to the similarity between Partial Evaluation (PE) and EBL. However, EBL utilizes training examples whereas PE does not. It is natural to inquire, therefore, whether PE can be used to acquire searchcontrol knowledge, and if so at what cost? This ...

The ability of case-based reasoning (CBR) systems to apply cases to novel situations depends on their case adaptation knowledge. However, endowing CBR systems with adequate adaptation knowledge has proven to be a very di cult task. This paper describes a hybrid method for performing case adaptation, using a combination of rule-based and case-based reasoning. It shows how this approach provides ...