We address the problem of evaluating textual task-oriented dialogues between the customer and the helpdesk, such as those that take the form of online chats. As an initial step towards evaluating automatic helpdesk dialogue systems, we have constructed a test collection comprising 3,700 real Customer-Helpdesk multi-turn dialogues by mining Weibo, a major Chinese social media. We have annotated each dialogue with multiple subjective quality annotations and nugget annotations, where a nugget is a minimal sequence of posts by the same utterer that helps towards problem solving. In addition 10% of the dialogues have been manually translated into English. We have made our test collection DCH-1 publicly available for research purposes. We also propose a simple nugget-based evaluation measure for task-oriented dialogue evaluation, which we call UCH, and explore its usefulness and limitations.
|ジャーナル||CEUR Workshop Proceedings|
|出版ステータス||Published - 2017|
|イベント||8th International Workshop on Evaluating Information Access, EVIA 2017 - Tokyo, Japan|
継続期間: 2017 12 5 → …
ASJC Scopus subject areas
- Computer Science(all)