@inproceedings{li-etal-2024-analyzing,
title = "Analyzing and Enhancing Clarification Strategies for Ambiguous References in Consumer Service Interactions",
author = "Li, Changling and
Gan, Yujian and
Yang, Zhenrong and
Chen, Youyang and
Qiu, Xinxuan and
Lin, Yanni and
Purver, Matthew and
Poesio, Massimo",
editor = "Kawahara, Tatsuya and
Demberg, Vera and
Ultes, Stefan and
Inoue, Koji and
Mehri, Shikib and
Howcroft, David and
Komatani, Kazunori",
booktitle = "Proceedings of the 25th Annual Meeting of the Special Interest Group on Discourse and Dialogue",
month = sep,
year = "2024",
address = "Kyoto, Japan",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.sigdial-1.25",
pages = "289--296",
abstract = "When customers present ambiguous references, service staff typically need to clarify the customers{'} specific intentions. To advance research in this area, we collected 1,000 real-world consumer dialogues with ambiguous references. This dataset will be used for subsequent studies to identify ambiguous references and generate responses. Our analysis of the dataset revealed common strategies employed by service staff, including directly asking clarification questions (CQ) and listing possible options before asking a clarification question (LCQ). However, we found that merely using CQ often fails to fully satisfy customers. In contrast, using LCQ, as well as recommending specific products after listing possible options, proved more effective in resolving ambiguous references and enhancing customer satisfaction.",
}
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<abstract>When customers present ambiguous references, service staff typically need to clarify the customers’ specific intentions. To advance research in this area, we collected 1,000 real-world consumer dialogues with ambiguous references. This dataset will be used for subsequent studies to identify ambiguous references and generate responses. Our analysis of the dataset revealed common strategies employed by service staff, including directly asking clarification questions (CQ) and listing possible options before asking a clarification question (LCQ). However, we found that merely using CQ often fails to fully satisfy customers. In contrast, using LCQ, as well as recommending specific products after listing possible options, proved more effective in resolving ambiguous references and enhancing customer satisfaction.</abstract>
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%0 Conference Proceedings
%T Analyzing and Enhancing Clarification Strategies for Ambiguous References in Consumer Service Interactions
%A Li, Changling
%A Gan, Yujian
%A Yang, Zhenrong
%A Chen, Youyang
%A Qiu, Xinxuan
%A Lin, Yanni
%A Purver, Matthew
%A Poesio, Massimo
%Y Kawahara, Tatsuya
%Y Demberg, Vera
%Y Ultes, Stefan
%Y Inoue, Koji
%Y Mehri, Shikib
%Y Howcroft, David
%Y Komatani, Kazunori
%S Proceedings of the 25th Annual Meeting of the Special Interest Group on Discourse and Dialogue
%D 2024
%8 September
%I Association for Computational Linguistics
%C Kyoto, Japan
%F li-etal-2024-analyzing
%X When customers present ambiguous references, service staff typically need to clarify the customers’ specific intentions. To advance research in this area, we collected 1,000 real-world consumer dialogues with ambiguous references. This dataset will be used for subsequent studies to identify ambiguous references and generate responses. Our analysis of the dataset revealed common strategies employed by service staff, including directly asking clarification questions (CQ) and listing possible options before asking a clarification question (LCQ). However, we found that merely using CQ often fails to fully satisfy customers. In contrast, using LCQ, as well as recommending specific products after listing possible options, proved more effective in resolving ambiguous references and enhancing customer satisfaction.
%U https://aclanthology.org/2024.sigdial-1.25
%P 289-296
Markdown (Informal)
[Analyzing and Enhancing Clarification Strategies for Ambiguous References in Consumer Service Interactions](https://aclanthology.org/2024.sigdial-1.25) (Li et al., SIGDIAL 2024)
ACL
- Changling Li, Yujian Gan, Zhenrong Yang, Youyang Chen, Xinxuan Qiu, Yanni Lin, Matthew Purver, and Massimo Poesio. 2024. Analyzing and Enhancing Clarification Strategies for Ambiguous References in Consumer Service Interactions. In Proceedings of the 25th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pages 289–296, Kyoto, Japan. Association for Computational Linguistics.