Inductive Logic Programming (ILP) has been shown to be a viable approach to many problems in multi-relational data mining (e.g. bioinformatics). Link discovery (LD) is an important task in data mining for counter-terrorism and is the focus of DARPA's program on Evidence Extraction and Link Discovery (EELD). Learning patterns for LD is a novel problem in relational data mining that is characteri...

Improvements over recent years in the performance of Integer Linear Programming (ILP) and Boolean Satisfiability (SAT) solvers have encouraged the modeling of complex engineering problems as ILP. An example is the Clustering Problem in Mobile Ad-Hoc Networks (MANETs). The Clustering Problem in MANETs consists of selecting the most suitable nodes of a given MANET topology as clusterheads, and en...

A nonlinear mathematical model was developed and experimentally validated to investigate the effects of changes in optical properties during interstitial laser photocoagulation (ILP). The effects of dynamic optical properties were calculated using the Arrhenius damage model, resulting in a nonlinear optothermal response. This response was experimentally validated by measuring the temperature ri...

This report describes the design and the prototyping of a compiling tool for the automated implementation of distributed applications: ALFred. This compiler starts from the formal specification of an application written in ESTEREL, and then integrates end-to-end communication functions tailored to the application characteristics (described in the specification) and produces a high performance i...

This paper introduces a new Inductive Logic Programming (ILP) framework called Top Directed Hypothesis Derivation (TDHD). In this framework each hypothesised clause must be derivable from a given logic program called top theory (>). The top theory can be viewed as a declarative bias which defines the hypothesis space. This replaces the metalogical mode statements which are used in many ILP syst...

We use Inductive Logic Programming (ILP) within a chart-parsing framework for grammar learning. Given an existing grammar G, together with some sentences which G can not parse, we use ILP to nd the \miss-ing" grammar rules or lexical items. Our aim is to exploit the inductive capabilities of chart parsing, i.e. the ability to eeciently determine what is needed for a parse. For each unparsable s...

Isolated lung perfusion (ILP) has been historically used as a method to study basic lung physiologic concepts using animal models. More recently, ILP has been applied in lung transplantation and thoracic oncology. In lung transplantation, ILP has been used to assess physiological integrity of donor lungs after the organ is removed from the donor. This procedure is called Ex vivo Lung Perfusion ...

Inductive Logic Programming (ILP) systems construct explanations for data in terms of domain-speciic background information. How does the quality of this information aaect the performance of an ILP system? Results from experiments concerned with learning simple programs for list processing suggest that performance is sensitive to the type and amount of background knowledge provided. In particul...

The goal of inductive logic programming (ILP) is to search for a hypothesis that generalises training examples and background knowledge (BK). To improve performance, we introduce an approach that, before searching hypothesis, first discovers "where not search". We use given BK discover constraints on hypotheses, such as number cannot be both even odd. the bootstrap constraint-driven ILP system....

Industry is increasingly overwhelmed by large-volume-data. For example, the pharmaceutical industry generates vast quantities of data both internally as a side-eeect of screening tests and combinato-rial chemistry, as well as externally from sources such as the human genome project. Industry is also becoming predominantly knowledge-driven. Increased understanding not only improves products, but...