Inductive Logic Programming (ILP) combines both Machine Learning and Logic Programming techniques. ILP uses rst-order predicate logic restricted to Horn clauses as an underlying language. Thus, programs induced by an ILP system inherit the classical limitations of PROLOG programs. Constraint Logic Programming avoids some of the limitations of Logic Programming and so ILP aims to induce programs...

Inductive Logic Programming (ILP) is a Machine Learning technique that has been quite successful in knowledge discovery for relational domains. ILP systems implemented in Prolog challenge the limits of Prolog systems due to heavy usage of resources such as database accesses and memory usage, and to very long execution times. The major reason to implement ILP systems in Prolog is that the infere...

The main idea of contrastive analysis, as propounded by Robert Lado in his book Linguistics Across Cultures (1957), was that it is possible to identify the areas of difficulty a particular foreign language will present for native speakers of another language by systematically comparing the two languages and cultures. Where the two languages and cultures are similar, learning difficulties will n...

Intron length polymorphisms (ILPs) have been used as genetic markers in some studies. However, a systematic investigation and large-scale exploitation of ILP markers has not been reported. In this study, we performed a genome-wide search of ILPs between two subspecies (indica and japonica) in rice using the draft genomic sequences of cultivars 93-11 (indica) and Nipponbare (japonica) and 32,127...

A key problem in QSAR is the selection of appropriate descriptors to form accurate regression equations for the compounds under study. Inductive Logic Programming (ILP) algorithms are a class of machine learning algorithm that have been successfully applied to a number of SAR problems. Unlike other QSAR methods, which use attributes to describe chemical structure, ILP uses relations. This gives...

Pragmatics is everywhere in life, and now pragmatics has formed a trend of combining with other disciplines. As newly developed discipline, brings new perspective to the development English language literature. This thesis mainly studies definition, branches future trends pragmatics, which can provide some reference for interdisciplinary research.

We present stable ILP, a cross-disciplinary concept straddling machine learning and nonmonotonic reasoning. Stable models give meaning to logic programs containing negative assertions. In stable ILP, we employ stable models to represent the current state speciied by (possibly) negative EDB and IDB rules. The state then serves as the background knowledge for a top-down ILP learner. We present a ...

We present stable ILP, a cross-disciplinary concept straddling machine learning and nonmonotonic reasoning. Stable models give meaning to logic programs containing negative assertions. In stable ILP, we employ stable models to represent the current state speciied by (possibly) negative EDB and IDB rules. The state then serves as the background knowledge for a top-down ILP learner. We present a ...

Formal Pragmatics discusses various topics that are at the borderline of the semantics and pragmatics of natural language, in particular the treatment of indefinites and anaphora, presuppositions, and the analysis of focus. Enormous progress has been made in the last two decades in the analysis of these phenomena. It is time for this body of work to be summarized and described in a relatively e...

This paper aims to show how clinical pragmatics (the study of pragmatic deficits) can fruitfully inform the classical theoretical models proposed by philosophical pragmatics. In the first part of the paper I argue that theories proposed in the domain of philosophical pragmatics, as those elaborated by Austin and Grice, are not plausible from a cognitive point of view and that for this reason th...