Abstract Data Mining and Knowledge Discovery in Databases (KDD) is a research field
concerned with deriving higher-level insights from data. The tasks performed in that field are …

Abstract Linked Open Data has been recognized as a valuable source for background
information in data mining. However, most data mining tools require features in propositional …

Abstract Linked Open Data has been recognized as a valuable source for background
information in many data mining and information retrieval tasks. However, most of the …

Lots of data from different domains are published as Linked Open Data (LOD). While there
are quite a few browsers for such data, as well as intelligent tools for particular purposes, a …

Knowledge Graphs have been recognized as a valuable source for background information
in many data mining, information retrieval, natural language processing, and knowledge …

Feature selection is an important preprocessing step in data mining, which has an impact on
both the runtime and the result quality of the subsequent processing steps. While there are …

We present an approach to efficiently construct stepwise regression models in a very high
dimensional setting using a multidimensional index. The approach is based on an …

Knowledge graphs have evolved as flexible and powerful means for representing general
world knowledge. Typical examples are DBpedia, Yago, or the Google Knowledge Graph …

In this paper, we discuss the development of a hybrid multi-strategy book recommendation
system using Linked Open Data. Our approach builds on training individual base …

Linked Open Data has been recognized as a valuable source for background information in
data mining. However, most data mining tools require features in propositional form, ie …