Semantic Tagging Using Topic Models Exploiting Wikipedia Category Network
In this paper we propose a probabilistic topic model that incorporates DBpedia knowledge into the topic model for tagging Web pages and online documents with topics discovered in them. Our method is based on integration of the DBpedia hierarchical category network with statistical topic models where DBpedia categories are considered as topics. We have conducted extensive experiments on two different datasets to demonstrate the effectiveness of our method.
2016 IEEE Tenth International Conference on Semantic Computing (ICSC)