The evaluation of semantic relatedness between web resources is still an open challenge.
This paper focuses on knowledge-based methods that provide an alternative to corpus …

The recent development of deep learning approaches provides a convenient way to learn
entity embeddings from different aspects such as texts and a homogeneous or …

Semantic Web and Linked Open Data (LOD) made the data readable by machines and
users. LOD, the set of principles for publishing and linking structured data on the web, opens …

The emergence of online social networks (OSNs) and linked open data (LOD) bring up
opportunities to experiment on a new generation of cross-domain recommender systems in …

Recommender systems can utilize Linked Open Data (LOD) to overcome some challenges,
such as the item cold start problem, as well as the problem of explaining the …

Data published on the web following the principles of linked data has resulted in a global
data space called the Web of Data. These principles led to semantically interlink and …

Abstract The use of Linked Open Data (LOD) has been explored in recommender systems in
different ways, primarily through its graphical representation. The graph structure of LOD is …

Abstract The use of Linked Open Data (LOD) has been explored in recommender systems in
different ways, primarily through its graphical representation. The graph structure of LOD is …

Linked Data has become a valuable source of factual records. However, because of its
simple representations of records (ie, a set of triples), learning representations of entities is …

Linked Data allows structured data to be published in a standard way that datasets from
various domains can be interlinked. With the rapid evolution of Linked Open Data (LOD) …