The World Wide Web is moving from a Web of hyper-linked documents to a Web of linked data. Thanks to the Semantic Web technological stack and to the more recent Linked Open Data (LOD) initiative, a vast amount of RDF data have been published in freely accessible datasets connected with each other to form the so called LOD cloud. As of today, we have tons of RDF data available in the Web of Data, but only a few applications really exploit their potential power. The availability of such data is for sure an opportunity to feed personalized information access tools such as recommender systems. We present an overview on recommender systems and we sketch how to use Linked Open Data to build a new generation of semantics-aware recommendation engines.
|Autori interni:||DI NOIA, Tommaso|
OSTUNI, Vito Claudio
|Titolo:||Recommender Systems and Linked Open Data|
|Titolo del libro:||11th International Reasoning Web Summer School, RW 2015|
|Data di pubblicazione:||2015|
|Appare nelle tipologie:||2.1 Contributo in volume (Capitolo o Saggio)|