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 many data mining and information retrieval tasks. However, most of the …

Abstract Information technology has spread widely, and extraordinarily large amounts of
data have been made accessible to users, which has made it challenging to select data that …

In the past few decades recommender system has reshaped the way of information filtering
between websites and the users. It helps in identifying user interest and generates product …

Thanks to the recent spread of the Linked Open Data (LOD) initiative, a huge amount of
machine-readable knowledge encoded as RDF statements is today available in the so …

In this paper, we present a strategy to provide users with knowledge-aware
recommendations based on the combination of graph neural networks and sentence …

In this paper, we present a knowledge-aware recommendation framework based on neuro-
symbolic graph embeddings that encode first-order logical (FOL) rules. In particular, our …

Movie recommendation systems are important tools that suggest films with respect to users'
choices through item-based collaborative filter algorithms, and have shown positive effect on …

In this chapter we present a report of the ESWC 2014 Challenge on Linked Open Data-
enabled Recommender Systems, which consisted of three tasks in the context of book …

In light of the global proliferation of the COVID-19 pandemic, there is a notable surge in
public interest towards Massive Open Online Courses (MOOCs) recently. Within the realm of …