Abstract. The combination of linked data and machine learning is emerging as an interesting area of research. However, while both fields have seen an exponential growth in popularity in the past decade, their union has received relatively little attention. We suggest that the field is currently too complex and divergent to allow collaboration and to at-tract new researchers. What is needed is a simple perspective, based on unifying principles. Focusing solely on RDF, with all other semantic web technology as optional additions is an important first step. We hope that this view will provide a low-complexity outline of the field to entice new contributions, and to unify existing ones.
In recent years, enormous progress has been made in the field of Artificial Intelligence (AI). Espec...
The discovery of useful data for a given problem is of primary importance since data scientists usua...
Book chapterIn this chapter, we first perform an empirical survey of RDF-based applications over mos...
The combination of linked data and machine learning is emerging as an interesting area of research. ...
It seems as though everyone is talking about Linked Data and the related Semantic Web these days. I...
With linked data, a very pragmatic approach towards achieving the vision of the semantic web has gai...
It seems as though everyone is talking about Linked Data and the related Semantic Web these days. In...
The effort to transform and extend data is a growing business in many industries. Proprietary data f...
Abstract — The Linked (Open) Data (LD/LOD) strategy extends the Web by publishing various open datas...
The Web is increasingly understood as a global information space consisting not just of linked docum...
Linked Open Data (LOD) is the publicly available RDF data in the Web. Each LOD entity is identfied b...
Abstract. Today’s most popular means for publishing semantic information on the web is the paradigm ...
The goal of this master thesis is to create a "manual" to Linked Data technology. The first part of ...
The paper defines the linked data as a set of best practices that are used to publish data on the we...
In recent years, enormous progress has been made in the field of Artificial Intelligence (AI). Espec...
The discovery of useful data for a given problem is of primary importance since data scientists usua...
Book chapterIn this chapter, we first perform an empirical survey of RDF-based applications over mos...
The combination of linked data and machine learning is emerging as an interesting area of research. ...
It seems as though everyone is talking about Linked Data and the related Semantic Web these days. I...
With linked data, a very pragmatic approach towards achieving the vision of the semantic web has gai...
It seems as though everyone is talking about Linked Data and the related Semantic Web these days. In...
The effort to transform and extend data is a growing business in many industries. Proprietary data f...
Abstract — The Linked (Open) Data (LD/LOD) strategy extends the Web by publishing various open datas...
The Web is increasingly understood as a global information space consisting not just of linked docum...
Linked Open Data (LOD) is the publicly available RDF data in the Web. Each LOD entity is identfied b...
Abstract. Today’s most popular means for publishing semantic information on the web is the paradigm ...
The goal of this master thesis is to create a "manual" to Linked Data technology. The first part of ...
The paper defines the linked data as a set of best practices that are used to publish data on the we...
In recent years, enormous progress has been made in the field of Artificial Intelligence (AI). Espec...
The discovery of useful data for a given problem is of primary importance since data scientists usua...
Book chapterIn this chapter, we first perform an empirical survey of RDF-based applications over mos...