Abstract. One of the de ning challenges for the KDD research community is to enable inductive learning algorithms to mine very large databases. This paper summarizes, categorizes, ...
Inductive Logic Programming (ILP) is a combination of inductive learning and first-order logic aiming to learn first-order hypotheses from training examples. ILP has a serious b...
The use of background knowledge and the adoption of Horn clausal logic as a knowledge representation and reasoning framework are the distinguishing features of Inductive Logic Prog...
The major challenge in mining data streams is the issue of concept drift, the tendency of the underlying data generation process to change over time. In this paper, we propose a g...
Extracting knowledge from unstructured text is a long-standing goal of NLP. Although learning approaches to many of its subtasks have been developed (e.g., parsing, taxonomy induc...