FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2964152081> ?p ?o ?g. }

• W2964152081 abstract "Our goal is to combine the rich multi-step inference of symbolic logical reasoning with the generalization capabilities of neural networks. We are particularly interested in complex reasoning about entities and relations in text and large-scale knowledge bases (KBs). Neelakantan et al. (2015) use RNNs to compose the distributed semantics of multi-hop paths in KBs; however for multiple reasons, the approach lacks accuracy and practicality. This paper proposes three significant modeling advances: (1) we learn to jointly reason about relations, entities, and entity-types; (2) we use neural attention modeling to incorporate multiple paths; (3) we learn to share strength in a single RNN that represents logical composition across all relations. On a large-scale Freebase+ClueWeb prediction task, we achieve 25% error reduction, and a 53% error reduction on sparse relations due to shared strength. On chains of reasoning in WordNet we reduce error in mean quantile by 84% versus previous state-of-the-art." @default.
• W2964152081 created "2019-07-30" @default.
• W2964152081 creator A5008354502 @default.
• W2964152081 creator A5043840749 @default.
• W2964152081 creator A5054325458 @default.
• W2964152081 creator A5086442444 @default.
• W2964152081 date "2017-01-01" @default.
• W2964152081 modified "2023-10-12" @default.
• W2964152081 title "Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks" @default.
• W2964152081 cites W114118985 @default.
• W2964152081 cites W1532325895 @default.
• W2964152081 cites W1533230146 @default.
• W2964152081 cites W1543747524 @default.
• W2964152081 cites W1756422141 @default.
• W2964152081 cites W175897666 @default.
• W2964152081 cites W1800356822 @default.
• W2964152081 cites W1852412531 @default.
• W2964152081 cites W1859383741 @default.
• W2964152081 cites W1884290075 @default.
• W2964152081 cites W1950142954 @default.
• W2964152081 cites W205829674 @default.
• W2964152081 cites W2077054525 @default.
• W2964152081 cites W2101848544 @default.
• W2964152081 cites W2102363952 @default.
• W2964152081 cites W2103729963 @default.
• W2964152081 cites W2127426251 @default.
• W2964152081 cites W2140310134 @default.
• W2964152081 cites W2250635077 @default.
• W2964152081 cites W2251960799 @default.
• W2964152081 cites W2460319482 @default.
• W2964152081 cites W2465041517 @default.
• W2964152081 cites W2511805592 @default.
• W2964152081 cites W2526662185 @default.
• W2964152081 cites W2913340405 @default.
• W2964152081 cites W2963380480 @default.
• W2964152081 cites W2964121744 @default.
• W2964152081 cites W2964224278 @default.
• W2964152081 cites W2964236999 @default.
• W2964152081 doi "https://doi.org/10.18653/v1/e17-1013" @default.
• W2964152081 hasPublicationYear "2017" @default.
• W2964152081 type Work @default.
• W2964152081 sameAs 2964152081 @default.
• W2964152081 citedByCount "171" @default.
• W2964152081 countsByYear W29641520812016 @default.
• W2964152081 countsByYear W29641520812017 @default.
• W2964152081 countsByYear W29641520812018 @default.
• W2964152081 countsByYear W29641520812019 @default.
• W2964152081 countsByYear W29641520812020 @default.
• W2964152081 countsByYear W29641520812021 @default.
• W2964152081 countsByYear W29641520812022 @default.
• W2964152081 countsByYear W29641520812023 @default.
• W2964152081 crossrefType "proceedings-article" @default.
• W2964152081 hasAuthorship W2964152081A5008354502 @default.
• W2964152081 hasAuthorship W2964152081A5043840749 @default.
• W2964152081 hasAuthorship W2964152081A5054325458 @default.
• W2964152081 hasAuthorship W2964152081A5086442444 @default.
• W2964152081 hasBestOaLocation W29641520811 @default.
• W2964152081 hasConcept C111335779 @default.
• W2964152081 hasConcept C119857082 @default.
• W2964152081 hasConcept C134306372 @default.
• W2964152081 hasConcept C147168706 @default.
• W2964152081 hasConcept C154945302 @default.
• W2964152081 hasConcept C157659113 @default.
• W2964152081 hasConcept C162324750 @default.
• W2964152081 hasConcept C177148314 @default.
• W2964152081 hasConcept C184337299 @default.
• W2964152081 hasConcept C187736073 @default.
• W2964152081 hasConcept C199360897 @default.
• W2964152081 hasConcept C204321447 @default.
• W2964152081 hasConcept C2524010 @default.
• W2964152081 hasConcept C2776214188 @default.
• W2964152081 hasConcept C2780451532 @default.
• W2964152081 hasConcept C33923547 @default.
• W2964152081 hasConcept C41008148 @default.
• W2964152081 hasConcept C50644808 @default.
• W2964152081 hasConceptScore W2964152081C111335779 @default.
• W2964152081 hasConceptScore W2964152081C119857082 @default.
• W2964152081 hasConceptScore W2964152081C134306372 @default.
• W2964152081 hasConceptScore W2964152081C147168706 @default.
• W2964152081 hasConceptScore W2964152081C154945302 @default.
• W2964152081 hasConceptScore W2964152081C157659113 @default.
• W2964152081 hasConceptScore W2964152081C162324750 @default.
• W2964152081 hasConceptScore W2964152081C177148314 @default.
• W2964152081 hasConceptScore W2964152081C184337299 @default.
• W2964152081 hasConceptScore W2964152081C187736073 @default.
• W2964152081 hasConceptScore W2964152081C199360897 @default.
• W2964152081 hasConceptScore W2964152081C204321447 @default.
• W2964152081 hasConceptScore W2964152081C2524010 @default.
• W2964152081 hasConceptScore W2964152081C2776214188 @default.
• W2964152081 hasConceptScore W2964152081C2780451532 @default.
• W2964152081 hasConceptScore W2964152081C33923547 @default.
• W2964152081 hasConceptScore W2964152081C41008148 @default.
• W2964152081 hasConceptScore W2964152081C50644808 @default.
• W2964152081 hasLocation W29641520811 @default.
• W2964152081 hasLocation W29641520812 @default.
• W2964152081 hasOpenAccess W2964152081 @default.
• W2964152081 hasPrimaryLocation W29641520811 @default.
• W2964152081 hasRelatedWork W1519502414 @default.
• W2964152081 hasRelatedWork W2151447942 @default.
• W2964152081 hasRelatedWork W2611614995 @default.

• next