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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 1 of 1 1 Recurrent One-Hop Predictions for Reasoning over Knowledge Graphs Isabelle, Pierre; Bender, Emily M.; Schütze, Hinrich; Derczynski, Leon; Yin, Wenpeng; Yaghoobzadeh, Yadollah. - : Ludwig-Maximilians-Universität München, 2018 Abstract: Large scale knowledge graphs (KGs) such as Freebase are generally incomplete. Reasoning over multi-hop (mh) KG paths is thus an important capability that is needed for question answering or other NLP tasks that require knowledge about the world. mh-KG reasoning includes diverse scenarios, e.g., given a head entity and a relation path, predict the tail entity; or given two enti- ties connected by some relation paths, predict the unknown relation between them. We present ROPs, recurrent one-hop predictors, that predict entities at each step of mh-KB paths by using recurrent neural networks and vector representations of entities and relations, with two benefits: (i) modeling mh-paths of arbitrary lengths while updating the entity and relation representations by the training signal at each step; (ii) handling different types of mh-KG reasoning in a unified framework. Our models show state-of-the-art for two important multi-hop KG reasoning tasks: Knowledge Base Completion and Path Query Answering Keyword: ddc:000; ddc:004; ddc:400; ddc:410 URL: https://epub.ub.uni-muenchen.de/61860/1/C18-1200.pdf https://doi.org/10.5282/ubm/epub.61860 http://nbn-resolving.de/urn:nbn:de:bvb:19-epub-61860-0 https://epub.ub.uni-muenchen.de/61860/ BASE Hide details

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