Quantified logic programs, revisited

We consider again quantified logic programs (QLP). QLP is a logic program where a positive number not greater than 1 called dominance is associated with each rule in the program. The intuition is that rules with higher dominance are more plausible or more reliable. Literals in the answer sets of QLPs are also annotated with weights, with the intuition that a literal with a higher weight is more likely to be true. We present three different applications of QLPs: Ontology Matching, Ranking of search results, and Inheritance Networks. We also address the problem of computing answer sets of QLPs. We show that we can compute the answer sets by first using existing state of the art tools for answer set generation, and then applying a polynomial time forward-chaining like algorithm, called the Proof-Rank Algorithm in order to compute the weight of each literal in the answer set.