Papers with RDoC Tasks of

1 papers
BioNLP-OST 2019 RDoC Tasks: Multi-grain Neural Relevance Ranking Using Topics and Attention Based Query-Document-Sentence Interactions (D19-57)

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Challenge: Our best systems achieved 1st rank and scored 0.86 mAP and 0.58 macro average accuracy in Task-1 and Task-2 respectively.
Approach: They propose to use attention-based supervised neural topic model and SVM for retrieval and ranking of PubMed abstracts and to use BM25 and other relevance measures for re-ranking.
Outcome: The proposed system scored 0.86 mAP and 0.58 macro average accuracy in the RDoC Tasks of BioNLP-OST 2019 .

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