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Всего связей: 103278

Исходная сущность Тип источника Связь Целевая сущность Тип Paper ID
Deep Recurrent Neural Network method appliesTo Sentence Boundary Detection task 4592.0
Deep Recurrent Neural Network method improves F Score metric 4592.0
Deep Recurrent Neural Networks method achieves F1 Score metric 4477.0
Deep Recurrent Neural Networks method evaluatedIn SemEval 2010 Task 8 material 4477.0
Deep Recurrent Neural Networks method proposedFor Relation Classification task 4477.0
Deep Recurrent Setting method uses Multi Task Learning method 4308.0
Deep Reinforcement Learning method addresses Summarizing Salient Information task 21224.0
Deep Reinforcement Learning method appliedIn Intermittent Short Extension Ensemble method 34019.0
Deep Reinforcement Learning method appliesTo Dialog Manager material 38178.0
Deep Reinforcement Learning method appliesTo Dialogue Generation task 33597.0
Deep Reinforcement Learning method comparesWith Recent Interactive Summarization System otherentity 21224.0
Deep Reinforcement Learning method evaluatedIn Chinese Stock Market Datasets material 20847.0
Deep Reinforcement Learning method mapsTo State Representations otherentity 34938.0
Deep Reinforcement Learning method proposes Logical Neural Network method 31820.0
Deep Reinforcement Learning method usedFor Abstractive Summarization task 8906.0
Deep Reinforcement Learning method usedIn Augmented Tagger method 5373.0
Deep Reinforcement Learning Architecture method improves Goal Completion metric 42993.0
Deep Reinforcement Relevance Network method comparesWith Deep Q-Learning method 40361.0
Deep Reinforcement Relevance Network method evaluatedIn Text Games task 40361.0
Deep Representation Learning method appliesTo Scientific Discourse material 42490.0