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A Declarative Semantics for CLP with Qualification and Proximity
Uncertainty in Logic Programming has been investigated during the last
decades, dealing with various extensions of the classical LP paradigm and
different applications. Existing proposals rely on different approaches, such
as clause annotations based on uncertain truth values, qualification values as
a generalization of uncertain truth values, and unification based on proximity
relations. On the other hand, the CLP scheme has established itself as a
powerful extension of LP that supports efficient computation over specialized
domains while keeping a clean declarative semantics. In this paper we propose a
new scheme SQCLP designed as an extension of CLP that supports qualification
values and proximity relations. We show that several previous proposals can be
viewed as particular cases of the new scheme, obtained by partial
instantiation. We present a declarative semantics for SQCLP that is based on
observables, providing fixpoint and proof-theoretical characterizations of
least program models as well as an implementation-independent notion of goal
solutions.Comment: 17 pages, 26th Int'l. Conference on Logic Programming (ICLP'10
A Complete and Recursive Feature Theory
Various feature descriptions are being employed in logic programming
languages and constrained-based grammar formalisms. The common notational
primitive of these descriptions are functional attributes called features. The
descriptions considered in this paper are the possibly quantified first-order
formulae obtained from a signature of binary and unary predicates called
features and sorts, respectively. We establish a first-order theory FT by means
of three axiom schemes, show its completeness, and construct three elementarily
equivalent models. One of the models consists of so-called feature graphs, a
data structure common in computational linguistics. The other two models
consist of so-called feature trees, a record-like data structure generalizing
the trees corresponding to first-order terms. Our completeness proof exhibits a
terminating simplification system deciding validity and satisfiability of
possibly quantified feature descriptions.Comment: Short version appeared in the 1992 Annual Meeting of the Association
for Computational Linguistic
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