Exploiting prior knowledge and latent variable representations for the statistical modeling and probabilistic querying of large knowledge graphs

@inproceedings{Krompass2015ExploitingPK,
  title={Exploiting prior knowledge and latent variable representations for the statistical modeling and probabilistic querying of large knowledge graphs},
  author={Denis Krompass},
  year={2015}
}
Large knowledge graphs increasingly add great value to various applications that require machines to recognize and understand queries and their semantics, as in search or question answering systems. These applications include Google search, Bing search, IBM’s Watson, but also smart mobile assistants as Apple’s Siri, Google Now or Microsoft’s Cortana. Popular knowledge graphs like DBpedia, YAGO or Freebase store a broad range of facts about the world, to a large extent derived from Wikipedia… CONTINUE READING