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A relational instance-based learning algorithm, called Ribl, is motivated and developed in this paper. We argue that instancebased methods o er solutions to the often unsatisfactory behavior of current inductive logic programming (ILP) approaches in domains with continuous attribute values and in domains with noisy attributes and/or examples. Three research(More)
This paper presents a model-driven method for machine learning of inference rules, which involves both: 'learning by induction' and 'learning by being told'. By the use of higher concepts (like transitivity and conversity) attributes of and relations among two-place predicates are discovered by induction. This new knowledge is represented as metafacts which(More)
This paper deals with the problem of learning characteristic concept descriptions from examples and describes a new generalization approach implemented in the system Cola-2. The approach tries to take advantage of the information which can be induced from descriptions of unclassiied objects using a conceptual clustering algorithm. Experimental results in(More)
The successful application of data mining techniques ideally requires both system support for the entire knowledge discovery process and the right analysis algorithms for the particular task at hand. While there are a number of successful data mining systems that support the entire mining process, they usually are limited to a fixed selection of analysis(More)
This paper presents a novel idea to the problem of learning concept descriptions from examples. Whereas most existing approaches rely on a large number of classiied examples, the approach presented in the paper is aimed at being applicable when only a few examples are classiied as positive (and negative) instances of a concept. The approach tries to take(More)
Knowledge revision in incremental learning systems w i l l usually be restr icted by some external c r i t e r i a to achieve a conservative behavior of the system. Unfortunately, conservatism has some well known drawbacks. Therefore, it can become necessary to drop these restr ict ions and to change over to a non-cumulative learning mode. In this paper the(More)
In this paper we present an overview of a project concerned with the configuration of telecommunication systems. The long term goal of this project is a fielded knowledge-based configuration system to support the work of consultants of the Deutsche Telekom AG. In this paper we analyze how and why the configuration of telecommunication systems differs from(More)