Conference Proceedings
HQADeepHelper: A Deep Learning System for Healthcare Question Answering
F Luo, X Wang, Q Wu, J Liang, X Qiu, Z Bao
Web Conference 2020 Companion of the World Wide Web Conference Www 2020 | ASSOC COMPUTING MACHINERY | Published : 2020
Abstract
It is challenging to generate high quality answers for healthcare queries in online platforms. Recent studies proposed deep models for healthcare question answering (HQA) tasks. However, these models have not been thoroughly compared, and they were only tested on self-created datasets. This paper demonstrates a novel system, denoted by HQADeepHelper, to facilitate the learning and practicing of deep models for HQA. We have implemented a wide spectrum of state-of-the-art deep models for HQA retrieval. Users can upload self-collected HQA datasets and knowledge graphs, and do simple configurations by selecting datasets, knowledge graphs, neural network models, and evaluation metrics. Based on u..
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Awarded by Google
Funding Acknowledgements
This work was supported by NSFC (61702432), the Fundamental Research Funds for Central Universities of China (20720180070) and the International Cooperation Projects of Fujian in China (2018I0016). Zhifeng Bao is supported in part by ARC DP200102611, DP180102050, NSFC 91646204, and a Google Faculty Award.