Combining multiple sources of informationis a major and diicult task in the management of uncertainty. Dempster's combination rule is one of the attractive approaches. However, many researchers have pointed out that the application domains of the rule are rather limited and it sometimes gives unexpected results. In this paper, we have further explored the nature of combination and achieved the ...

When more than a single classifier has been trained for the same recognition problem the question arises how this set of classifiers may be combined into a final decision rule. Several fixed combining rules are used that depend on the output values of the base classifiers only. They are almost always suboptimal. Usually, however, training sets are available. They may be used to calibrate the ba...

On the Semantic Web, there has been increasing demand for a ruleslike expressivity that goes beyond OWL-DL. Efforts of combining rules languages and description logics usually produce undecidable formalisms, unless constrained in a specific way. We look at one of the most expressive but decidable such formalisms proposed: DL-safe rules, and present a tableaux-based algorithm for query answering...

We report on several experiments on combining a rule-based tagger and a trigram tagger for Spanish. The results show that one can boost the accuracy of the best performing n-gram taggers by quickly developing a rough rule-based grammar to complement the statistically induced one and then combining the output of the two. The specific method of combination is crucial for achieving good results. T...

The potential outcome framework for causal inference is fundamentally a missing data problem with a special, the so-called file-matching, pattern of missing data. Given the large body of literature on various methods for handling missing data and associated software, it will be useful to use such methods to facilitate causal inference for routine applications. This article uses the sequential r...

Many real-world domains exhibit rich relational structure and stochasticity and motivate the development of models that combine predicate logic with probabilities. These models describe probabilistic influences between attributes of objects that are related to each other through known domain relationships. To keep these models succinct, each such influence is considered independent of others, w...

We survey existing approaches to the problem of combining rule languages with ontology languages for the Semantic Web. The focus is on the languages based on logic and on the reasoning in such languages. The objective is to give a uniform view of the approaches, and to outline related research topics important for REWERSE. Keyword List ontologies, ontology languages, description logics, datalog...

In this paper, we propose the CCAR (Combining Case-based And Rule-based reasoning) model for an exception handling of Rule-based Reasoning using Case-based Reasoning. The central idea of the model proposed in this paper is to represent the exception of a rule as a case, and to utilize the case for a solution to a problem, and then to search the case memory to retrieve a case which violates the ...

A general top-down algorithmization for the WellFounded MKNF Semantics a semantics for combining rules and ontologies was recently defined based on an extension of SLG resolution for Logic Programming with an abstract oracle to the parametric ontology language. Here we provide a concrete oracle with practical usage, namely for EL which is tractable for reasoning tasks like subsumption. We show ...

Model calculations are presented that predict whether or not an arbitrary gas experiences significant absorption within carbon nanotubes and/or bundles of nanotubes. The potentials used in these calculations assume a conventional form, based on a sum of two-body interactions with individual carbon atoms; the latter employ energy and distance parameters that are derived from empirical combining ...