Exploiting the Web of Data in Model-based Recommender Systems

6th ACM Conference on Recommender Systems (RecSys 2012) - 2012
Download the publication : rec157-dinoia.pdf [377Ko]  
The availability of a huge amount of interconnected data in the so called Web of Data (WoD) paves the way to a new generation of applications able to exploit the information encoded in it. In this paper we present a model-based recommender system leveraging the datasets publicly available in the Linked Open Data (LOD) cloud as DBpedia and LinkedMDB. The proposed approach adapts support vector machine (SVM) to deal with RDF triples. We tested our system and showed its effectiveness by a comparison with different recommender systems techniques - both content-based and collaborative-filtering ones.

BibTex references

author = {Tommaso {Di Noia} and Roberto Mirizzi and Vito Claudio Ostuni and Davide Romito},
title = "Exploiting the Web of Data in Model-based
Recommender Systems",
booktitle = "6th ACM Conference on Recommender Systems (RecSys
year = "2012",
publisher = "ACM Press",
organization = "ACM",
url = "http://www-ictserv.poliba.it/publications/2012/DMO

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SisInf Lab - Information Systems Laboratory

Research group of Politecnico di Bari
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