The development of natural language processing algorithms and the explosive growth of conversational data are encouraging researches on the human-computer conversation. Still, getting qualified conversational data on a large scale is difficult and expensive. In this paper, we verify the feasibility of constructing a data-driven chatbot with processed online community posts by using them as pseudo-conversational data. We argue that chatbots for various purposes can be built extensively through the pipeline exploiting the common structure of community posts. Our experiment demonstrates that chatbots created along the pipeline can yield the proper responses.
@article{arxiv.2001.03278,
title = {A Scalable Chatbot Platform Leveraging Online Community Posts: A Proof-of-Concept Study},
author = {Sihyeon Jo and Seungryong Yoo and Sangwon Im and Seung Hee Yang and Tong Zuo and Hee-Eun Kim and SangWook Han and Seong-Woo Kim},
journal= {arXiv preprint arXiv:2001.03278},
year = {2020}
}
Comments
To be Published on the 10th February, 2020, in HCI (Human-Computer Interaction) Conference 2020, Republic of Korea