Cargando…
IARNN-Based Semantic-Containing Double-Level Embedding Bi-LSTM for Question-and-Answer Matching
We propose a novel end-to-end approach, namely, the semantic-containing double-level embedding Bi-LSTM model (SCDE-Bi-LSTM), to solve the three key problems of Q&A matching in the Chinese medical field. In the similarity calculation of the Q&A core module, we propose a text similarity calcul...
| Autores principales: | , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Hindawi
2019
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6421739/ https://www.ncbi.nlm.nih.gov/pubmed/30944556 http://dx.doi.org/10.1155/2019/6074840 |