An Experimental Evaluation of a Scalable Probabilistic Description Logic Approach for Semantic Link Prediction

José Eduardo Ochoa Luna, Kate Revoredo, Fábio Gagliardi Cozman
2012 International Semantic Web Conference  
In previous work, we presented an approach for link prediction using a probabilistic description logic, named crALC. Inference in crALC, considering all the social network individuals, was used for suggesting or not a link. Despite the preliminary experiments have shown the potential of the approach, it seems unsuitable for real world scenarios, since in the presence of a social network with many individuals and evidences about them, the inference was unfeasible. Therefore, we extended our
more » ... ach through the consideration of graph-based features to reduce the space of individuals used in inference. In this paper, we evaluate empirically this modification comparing it with standard proposals. It was possible to verify that this strategy does not decrease the quality of the results and makes the approach scalable.
dblp:conf/semweb/LunaRC12 fatcat:2ln25372ungxbecxwuju6rikwi