abstract
Inductive Logic Programming or ILP is a research area that has emerged in last thirty years. The idea that gave the bases for ILP is merging machine learning and logic programming, in that way we can extract the best of both technologies and overcome many of the limitations of its forebears. ILP paradigm allows new methods for machine learning, and it allows to investigates the inductive construction of first-order clausal theories from a knowledge base and sets of positive and negative examples for a specific domain. That clausal will compose the logic program who can generalise positive example and it can exclude negative example. The document realised is a Systematic Literature Review (SLR). SLR is a revision type that uses analytical and repeatable methods to collect and analyse data. In detail in the document will be analysed the theoretical basis of ILP, and the main approaches and technologies will be presented, described and compared.
keywords
ILP, Inductive Logic Prorgamming, Machine Learning, Logic programming, First Order Logic, Systematic Literature Review
outcomes
