8,039 research outputs found
Constraints on predicate invention
This chapter describes an inductive learning method that derives logic programs and invents predicates when needed. The basic idea is to form the least common anti-instance (LCA) of selected seed examples. If the LCA is too general it forms the starting poínt of a gneral-to-specific search which is guided by various constraints on argument dependencies and critical terms. A distinguishing feature of the method is its ability to introduce new predicates. Predicate invention involves three steps. First, the need for a new predicate is discovered and the arguments of the new predicate are determíned using the same constraints that guide the search. In the second step, instances of the new predicate are abductively inferred. These instances form the input for the last step where the definition of the new predicate is induced by recursively applying the method again. We also outline how such a system could be more tightly integrated with an abductive learning system
Modular Web Queries — From Rules to Stores
Even with all the progress in Semantic technology, accessing Web
data remains a challenging issue with new Web query languages and approaches
appearing regularly. Yet most of these languages, including W3C approaches
such as XQuery and SPARQL, do little to cope with the explosion of the data
size and schemata diversity and richness on the Web. In this paper we propose
a straightforward step toward the improvement of this situation that is simple to
realize and yet effective: Advanced module systems that make partitioning of (a)
the evaluation and (b) the conceptual design of complex Web queries possible.
They provide the query programmer with a powerful, but easy to use high-level
abstraction for packaging, encapsulating, and reusing conceptually related parts
(in our case, rules) of a Web query. The proposed module system combines ease
of use thanks to a simple core concept, the partitioning of rules and their consequences
in flexible “stores”, with ease of deployment thanks to a reduction
semantics. We focus on extending the rule-based Semantic Web query language
Xcerpt with such a module system though the same approach can be applied to
other (rule-based) languages as well
Problem solving in ID-logic with aggregates: some experiments
The goal of the LP+ project at the K.U.Leuven is to design an expressive
logic, suitable for declarative knowledge representation, and to develop
intelligent systems based on Logic Programming technology for solving
computational problems using the declarative specifications. The ID-logic is an
integration of typed classical logic and a definition logic. Different
abductive solvers for this language are being developed. This paper is a report
of the integration of high order aggregates into ID-logic and the consequences
on the solver SLDNFA.Comment: 9 pages conference: NMR2000, special track on abductive reasonin
Constraint Logic Programming for Natural Language Processing
This paper proposes an evaluation of the adequacy of the constraint logic
programming paradigm for natural language processing. Theoretical aspects of
this question have been discussed in several works. We adopt here a pragmatic
point of view and our argumentation relies on concrete solutions. Using actual
contraints (in the CLP sense) is neither easy nor direct. However, CLP can
improve parsing techniques in several aspects such as concision, control,
efficiency or direct representation of linguistic formalism. This discussion is
illustrated by several examples and the presentation of an HPSG parser.Comment: 15 pages, uuencoded and compressed postscript to appear in
Proceedings of the 5th Int. Workshop on Natural Language Understanding and
Logic Programming. Lisbon, Portugal. 199
Ontology mapping: the state of the art
Ontology mapping is seen as a solution provider in today's landscape of ontology research. As the number of ontologies that are made publicly available and accessible on the Web increases steadily, so does the need for applications to use them. A single ontology is no longer enough to support the tasks envisaged by a distributed environment like the Semantic Web. Multiple ontologies need to be accessed from several applications. Mapping could provide a common layer from which several ontologies could be accessed and hence could exchange information in semantically sound manners. Developing such mapping has beeb the focus of a variety of works originating from diverse communities over a number of years. In this article we comprehensively review and present these works. We also provide insights on the pragmatics of ontology mapping and elaborate on a theoretical approach for defining ontology mapping
Memory-Based Learning: Using Similarity for Smoothing
This paper analyses the relation between the use of similarity in
Memory-Based Learning and the notion of backed-off smoothing in statistical
language modeling. We show that the two approaches are closely related, and we
argue that feature weighting methods in the Memory-Based paradigm can offer the
advantage of automatically specifying a suitable domain-specific hierarchy
between most specific and most general conditioning information without the
need for a large number of parameters. We report two applications of this
approach: PP-attachment and POS-tagging. Our method achieves state-of-the-art
performance in both domains, and allows the easy integration of diverse
information sources, such as rich lexical representations.Comment: 8 pages, uses aclap.sty, To appear in Proc. ACL/EACL 9
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