@inproceedings{liu2019a,
author = {LIU, Qian and Chen, Bei and LIU, Haoyan and Lou, Jian-Guang and Fang, Lei and ZHOU, Bin and Zhang, Dongmei},
title = {A Split-and-Recombine Approach for Follow-up Query Analysis},
booktitle = {EMNLP},
year = {2019},
month = {November},
abstract = {Context-dependent semantic parsing has proven to be an important yet challenging task. To leverage the advances in context-independent semantic parsing, we propose to perform follow-up query analysis, aiming to restate context-dependent natural language queries with contextual information. To accomplish the task, we propose STAR, a novel approach with a well-designed two-phase process. It is parser-independent and able to handle multifarious follow-up scenarios in different domains. Experiments on the FollowUp dataset show that STAR outperforms the state-of-the-art baseline by a large margin of nearly 8%. The superiority on parsing results verifies the feasibility of follow-up query analysis. We also explore the extensibility of STAR on the SQA dataset, which is very promising.},
url = {http://approjects.co.za/?big=en-us/research/publication/a-split-and-recombine-approach-for-follow-up-query-analysis/},
}