@inproceedings{du2020leveraging,
author = {Du, Xinya and Fourney, Adam and Sim, Robert and Bennett, Paul and Cardie, Claire and Awadallah, Ahmed},
title = {Leveraging Structured Metadata for Improving Question Answering on the Web},
booktitle = {AACL 2020},
year = {2020},
month = {December},
abstract = {We show that leveraging metadata information from web pages can improve the performance of models for answer passage selection/reranking. We propose a neural passage selection model that leverages metadata information with a fine-grained encoding strategy, which learns the representation for metadata predicates in a hierarchical way. The models are evaluated on the MS MARCO (Nguyen et al., 2016) and Recipe-MARCO datasets. Results show that our models significantly outperform baseline models, which do not incorporate metadata. We also show that the fine-grained encoding’s advantage over other strategies for encoding the metadata.},
url = {http://approjects.co.za/?big=en-us/research/publication/leveraging-structured-metadata-for-improving-question-answering-on-the-web/},
}