Analyzing and Characterizing User Intent in Information-seeking Conversations

被引：65

作者：

Qu, Chen ^{[1
]}

Yang, Liu ^{[1
]}

Croft, W. Bruce ^{[1
]}

Trippas, Johanne R. ^{[2
]}

Zhang, Yongfeng ^{[3
]}

Qiu, Minghui ^{[4
]}

机构：

[1] Univ Massachusetts Amherst, Amherst, MA 01003 USA

[2] RMIT Univ, Melbourne, Vic, Australia

[3] Rutgers State Univ, New Brunswick, NJ USA

[4] Alibaba Grp, Hangzhou, Zhejiang, Peoples R China

来源：

ACM/SIGIR PROCEEDINGS 2018 | 2018年

基金：

美国国家科学基金会;

关键词：

Information-seeking; Conversational Search; User Intent;

D O I：

10.1145/3209978.3210124

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Understanding and characterizing how people interact in information-seeking conversations is crucial in developing conversational search systems. In this paper, we introduce a new dataset designed for this purpose and use it to analyze information-seeking conversations by user intent distribution, co-occurrence, and flow patterns. The MSDialog dataset is a labeled dialog dataset of question answering (QA) interactions between information seekers and providers from an online forum on Microsoft products. The dataset contains more than 2,000 multi-turn QA dialogs with 10,000 utterances that are annotated with user intent on the utterance level. Annotations were done using crowdsourcing. With MSDialog, we find some highly recurring patterns in user intent during an information-seeking process. They could be useful for designing conversational search systems. We will make our dataset freely available to encourage exploration of information-seeking conversation models.

引用

页码：989 / 992

页数：4