We propose a new technique for normalizing likelihood of multiple classifiers prior to their combination. Our technique takes classifier-specific likelihood characteristics into account and maps them to a common, ideal characteristic allowing fair combination under arbitrary combination schemes. For each classifier, a simple warping process aligns the likelihood with the accumulated recognition...

The paper concerns the use of the lexicographic rule for combining preference relations with diierent priorities. We use it to interpret defaults with priorities. We present four kinds of results. We show that the lexicographic rule is the only way of combining preference relations which satisses conditions proposed by Arrow 1. We show in what circumstances the lexicographic rule propagates var...

This paper examines fundamental problems underlying difficulties encountered by pattern recognition algorithms, neural networks, and rule systems. These problems are manifested as combinatorial complexity of algorithms, of their computational or training requirements. The paper relates particular types of complexity problems to the roles of a priori knowledge and adaptive learning. Paradigms ba...

By the use of declarative rules, automation of tasks can be performed through an electronic personal information management (PIM) application. Rules can be used in a variety of different scenarios, for instance to trigger information retrieval tasks or to send out notifications when a pre-determined set of conditions are satisfied. The technology described is an integral part of the IBM Tempus ...

In this paper we propose the hybridisation of the rough set concepts and statistical learning theory. We introduce new estimators for rule accuracy and coverage, which base on the assumptions of the statistical learning theory. Then we construct classifier which uses these estimators for rule induction. These estimators allow us to select rules describing statistically significant dependencies ...

In this paper one proposes a simple algorithm of combining the fusion rules, those rules which first use the conjunctive rule and then the transfer of conflicting mass to the non-empty sets, in such a way that they gain the property of associativity and fulfill the Markovian requirement for dynamic fusion. Also, a new fusion rule, SDL-improved, is presented.

In this position paper we briefly present a semantic framework for investigating the problem of combining ontology and rule languages. We also show how rules are strictly related to queries. We claim that any choice of rule language for the semantic web should clearly define its semantics.

Legal texts express conditions in natural language describing what is permitted, forbidden or mandatory in the context they regulate. Despite the numerous approaches tackling the problem of moving from a natural language legal text to the respective set of machine-readable conditions, results are still unsatisfiable and it remains a major open challenge. In this paper, we propose a preliminary ...

An architecture is presented for combining rule-based and case-based reasoning. The architecture is intended for domains that are understood reasonably well, but still imperfectly. It uses a set of rules, which are taken to be only approximately correct, to obtain a preliminary answer for a given problem; it then draws analogies from cases to handle exceptions to the rules. Having rules togethe...