Active learning for cross-sentence n-ary relation extraction

Author:

Seo SeungminORCID,Oh ByungkookORCID,Jeoung Jeongbeom,Kim DonghyunORCID,Lee Kyong-Ho,Shin Dong-Hoon,Lee Yeonsoo

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference50 articles.

1. Incorporating anticipation embedding into reinforcement learning framework for multi-hop knowledge graph question answering;Cui;Inf. Sci.,2023

2. News recommendation with topic-enriched knowledge graphs;Lee,2020

3. Open-world knowledge graph completion for unseen entities and relations via attentive feature aggregation;Oh;Inf. Sci.,2022

4. Cross-sentence n-ary relation extraction with graph LSTMs;Peng;Trans. Assoc. Comput. Linguist.,2017

5. Graph convolution over pruned dependency trees improves relation extraction;Zhang,2018

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