A linear classification rule (used with equal covariance matrices) was contrasted with a quadratic rule (used with unequal covariance matrices) for accuracy of internal and external classification. The comparisons were made for seven situations which resulted from combining conditions (equal and unequal covariance matrices, and two and three criterion groups) for different sets of real data. Fo...

In this paper a new mathematical procedure is presented for combining different pieces of evidence which are represented in the interval form to reflect our knowledge about the truth of a hypothesis. Evidences may be correlated to each other (dependent evidences) or conflicting in supports (conflicting evidences). First, assuming independent evidences, we propose a methodology to construct comb...

The period character’s meaning is highly ambiguous due to the frequency of abbreviations that require to be followed by a period. We have developed a hybrid method for period character disambiguation and the identification of abbreviations, combining rules that explore regularities in the right context of the period with lexicon-based, statistical methods which scrutinize the preceding token. T...

The classical DPO graph rewriting construction is re-expressed using the oppbration approach introduced originally for term graph rewriting. Using a skeleton category of graphs, a base of canonical graphs-in-context, with DPO rules as arrows, and with categories of redexes over each object in the base, yields a category of rewrites via the discrete Grothendieck construction. The various possibl...

The combination of rules and ontologies has a central role in the ongoing development of the Semantic Web. In previous work, autoepistemic logic (AEL) was advocated as a uniform host formalism to study different such combinations, enabling comparisons on a common basis. In this paper, we continue this line of research and investigate different embeddings of major proposals to combine rules and ...

—Amidst the conflicting experimental evidence of superiority of one over the other, we investigate the Sum and majority Vote combining rules in a two class case, under the assumption of experts being of equal strength and estimation errors conditionally independent and identically distributed. We show, analytically, that, for Gaussian estimation error distributions, Sum always outperforms Vote....