Since the late 1970s, relational database technology has been adopted by most
organizations to store their essential data. However, nowadays, the needs of these …

In this paper, a novel machine learning model is proposed to predict the staying time of
international migrants. The competitive machine learning approaches which can be used to …

Knowledge graphs (KGs) represent facts in the form of subject-predicate-object triples and
are widely used to represent and share knowledge on the Web. Their ability to represent …

A major part of Open Data concerns statistics such as economic and social indicators.
Statistical data are structured in a multidimensional manner creating data cubes. Recently …

OLAP has been extensively used for a couple of decades as a data analysis approach to
support decision making on enterprise structured data. Now, with the wide diffusion of …

Exploratory OLAP aims at coupling the precision and detail of corporate data with the
information wealth of LOD. While some techniques to create, publish, and query RDF cubes …

In an increasingly competitive market, making well-informed decisions requires the analysis
of a wide range of heterogeneous, large and complex data. This paper focuses on the …

Due to their expressive power, Knowledge Graphs (KGs) have received increasing interest
not only as means to structure and integrate heterogeneous information but also as a native …

The popularity of the Semantic Web (SW) encourages organizations to organize and publish
semantic data using the RDF model. This growth poses new requirements to Business …

Large volumes of geospatial data are being published on the Semantic Web (SW), yielding
a need for advanced analysis of such data. However, existing SW technologies only support …