MindLab Neural Network Approach at BioASQ 6B

Andrés Rosso-Mateus, Fabio A. González, Manuel Montes-y-Gómez


Abstract
Biomedical Question Answering is concerned with the development of methods and systems that automatically find answers to natural language posed questions. In this work, we describe the system used in the BioASQ Challenge task 6b for document retrieval and snippet retrieval (with particular emphasis in this subtask). The proposed model makes use of semantic similarity patterns that are evaluated and measured by a convolutional neural network architecture. Subsequently, the snippet ranking performance is improved with a pseudo-relevance feedback approach in a later step. Based on the preliminary results, we reached the second position in snippet retrieval sub-task.
Anthology ID:
W18-5305
Volume:
Proceedings of the 6th BioASQ Workshop A challenge on large-scale biomedical semantic indexing and question answering
Month:
November
Year:
2018
Address:
Brussels, Belgium
Venues:
BioASQ | EMNLP | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
40–46
Language:
URL:
https://www.aclweb.org/anthology/W18-5305
DOI:
10.18653/v1/W18-5305
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PDF:
http://aclanthology.lst.uni-saarland.de/W18-5305.pdf