Inductive Logic Programming (ILP) has achieved considerablesuccess in a wide range of domains. It is recognized however thateciency is a major obstacle to the use of ILP systems in applicationsrequiring large amounts of data. In this paper we address the problem ofeciency in ILP in three steps: i) we survey speedup techniques proposedfor sequential execution of ILP systems; ii) we survey dierent ways ofparallelizing an ILP system and; ii) adapt and combine the sequentialexecution speedup techniques in the parallel implementations of an ILPsystem. We also propose a novel technique to partition the search spaceinto independent sub-spaces that may be adequately searched in parallel
We present new algorithms which perform automatic parallelization via source-to-source transformatio...
Inductive Logic Programming (ILP) systems aim to find a set of logical rules, called a hypothesis, t...
Machine Learning (ML) approaches can achieve impressive results, but many lack transparency or have ...
It is well known by Inductive Logic Programming (ILP) practionersthat ILP systems usually take a lon...
The generic task of Inductive Logic Programming (ILP) is to search a predefined subspace of first-or...
The amount of data collected and stored in databases is growing considerably for almost all areas of...
Inductive Logic Programming (ILP) is a promising technology for knowledgeextraction applications. IL...
Inductive Logic Programming (ILP) is a Machine Learning research field that has been quite successfu...
Inductive Logic Programming (ILP) is a powerful and welldeveloped abstraction for multi-relational d...
Inductive Logic Programming (ILP) is a promising technol-ogy for knowledge extraction applications. ...
We propose and evaluate a technique to improve the eciency of an ILP system. The technique avoids th...
AbstractWe address the problem of parallelizing the evaluation of logic programs in data intensive a...
IndLog is a general purpose Prolog-based Inductive Logic Programming (ILP) system. It is theoretical...
Inductive logic programming (ILP) is built on a foundation laid by research in machine learning and ...
1 Induction as a Search Procedure This chapter introduces Inductive Logic Programming from the persp...
We present new algorithms which perform automatic parallelization via source-to-source transformatio...
Inductive Logic Programming (ILP) systems aim to find a set of logical rules, called a hypothesis, t...
Machine Learning (ML) approaches can achieve impressive results, but many lack transparency or have ...
It is well known by Inductive Logic Programming (ILP) practionersthat ILP systems usually take a lon...
The generic task of Inductive Logic Programming (ILP) is to search a predefined subspace of first-or...
The amount of data collected and stored in databases is growing considerably for almost all areas of...
Inductive Logic Programming (ILP) is a promising technology for knowledgeextraction applications. IL...
Inductive Logic Programming (ILP) is a Machine Learning research field that has been quite successfu...
Inductive Logic Programming (ILP) is a powerful and welldeveloped abstraction for multi-relational d...
Inductive Logic Programming (ILP) is a promising technol-ogy for knowledge extraction applications. ...
We propose and evaluate a technique to improve the eciency of an ILP system. The technique avoids th...
AbstractWe address the problem of parallelizing the evaluation of logic programs in data intensive a...
IndLog is a general purpose Prolog-based Inductive Logic Programming (ILP) system. It is theoretical...
Inductive logic programming (ILP) is built on a foundation laid by research in machine learning and ...
1 Induction as a Search Procedure This chapter introduces Inductive Logic Programming from the persp...
We present new algorithms which perform automatic parallelization via source-to-source transformatio...
Inductive Logic Programming (ILP) systems aim to find a set of logical rules, called a hypothesis, t...
Machine Learning (ML) approaches can achieve impressive results, but many lack transparency or have ...