@article{zhu2019order-sensitive,
author = {Zhu, Qingfu and Zhang, Weinan and Cui, Lei and Liu, Ting},
title = {Order-Sensitive Keywords Based Response Generation in Open-Domain Conversational Systems},
year = {2019},
month = {August},
abstract = {External keywords are crucial for response generation models to address the generic response problems in open-domain conversational systems. The occurrence of keywords in a response depends heavily on the order of the keywords as they are generated sequentially. Meanwhile, the order of keywords also affects the semantics of a response. Previous keywords based methods mainly focus on the composite of keywords, while the order of keywords has not been sufficiently discussed. In this work, we propose an order-sensitive keywords based model to explore the influence of the order of keywords in open-domain response generation. It automatically inferences the most suitable order that is optimized to generate a natural and relevant response, and subsequently generates the response using the ordered keywords as building blocks. We conducted experiments on a public Twitter dataset and the results show that our approach outperforms the state-of-the-art baselines in both automatic and human evaluations.},
url = {http://approjects.co.za/?big=en-us/research/publication/order-sensitive-keywords-based-response-generation-in-open-domain-conversational-systems/},
journal = {ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP)},
}