Attention-Wrapped Hierarchical BLSTMs for DDI Extraction

Autor:	Mostafapour, Vahab, Dikenelli, Oğuz
Rok vydání:	2019
Předmět:	Computer Science - Information Retrieval Computer Science - Machine Learning Statistics - Machine Learning
Druh dokumentu:	Working Paper
Popis:	Drug-Drug Interactions (DDIs) Extraction refers to the efforts to generate hand-made or automatic tools to extract embedded information from text and literature in the biomedical domain. Because of restrictions in hand-made efforts and their lower speed, Machine-Learning, or Deep-Learning approaches have become more popular for extracting DDIs. In this study, we propose a novel and generic Deep-Learning model which wraps Hierarchical Bidirectional LSTMs with two Attention Mechanisms that outperforms state-of-the-art models for DDIs Extraction, based on the DDIExtraction-2013 corpora. This model has obtained the macro F1-score of 0.785, and the precision of 0.80. Comment: 7 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1907.13561 Zobrazit plný text záznamu View this record from Arxiv