Taking up the Gaokao Challenge: An Information Retrieval Approach
Abstract
Answering questions in a university's entrance examination like Gaokao in China challenges AI technology. As a preliminary attempt to take up this challenge, we focus on multiple-choice questions in Gaokao, and propose a three-stage approach that exploits and extends information retrieval techniques. Taking Wikipedia as the source of knowledge, our approach obtains knowledge relevant to a question by retrieving pages from Wikipedia via string matching and context-based disambiguation, and then ranks and filters pages using multiple strategies to draw critical evidence, based on which the truth of each option is assessed via relevance-based entailment. It achieves encouraging results on real-life questions in recent history tests, significantly outperforming baseline approaches. PDF
Cite
Text
Cheng et al. "Taking up the Gaokao Challenge: An Information Retrieval Approach." International Joint Conference on Artificial Intelligence, 2016.Markdown
[Cheng et al. "Taking up the Gaokao Challenge: An Information Retrieval Approach." International Joint Conference on Artificial Intelligence, 2016.](https://mlanthology.org/ijcai/2016/cheng2016ijcai-taking/)BibTeX
@inproceedings{cheng2016ijcai-taking,
title = {{Taking up the Gaokao Challenge: An Information Retrieval Approach}},
author = {Cheng, Gong and Zhu, Weixi and Wang, Ziwei and Chen, Jianghui and Qu, Yuzhong},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2016},
pages = {2479-2485},
url = {https://mlanthology.org/ijcai/2016/cheng2016ijcai-taking/}
}