Abstract
We address the task of sentence retrieval for open-ended dialogues. The goal is to retrieve sentences from a document corpus that contain information useful for generating the next turn in a given dialogue. Prior work on dialogue-based retrieval focused on specific types of dialogues: either conversational QA or conversational search. To address a broader scope of this task where any type of dialogue can be used, we constructed a dataset that includes open-ended dialogues from Reddit, candidate sentences from Wikipedia for each dialogue and human annotations for the sentences. We report the performance of several retrieval baselines, including neural retrieval models, over the dataset. To adapt neural models to the types of dialogues in the dataset, we explored an approach to induce a large-scale weakly supervised training data from Reddit. Using this training set significantly improved the performance over training on the MS MARCO dataset.
Original language | English |
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Title of host publication | SIGIR 2022 - Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval |
Publisher | Association for Computing Machinery, Inc |
Pages | 2960-2969 |
Number of pages | 10 |
ISBN (Electronic) | 9781450387323 |
DOIs | |
State | Published - 6 Jul 2022 |
Externally published | Yes |
Event | 45th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2022 - Madrid, Spain Duration: 11 Jul 2022 → 15 Jul 2022 |
Publication series
Name | SIGIR 2022 - Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval |
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Conference
Conference | 45th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2022 |
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Country/Territory | Spain |
City | Madrid |
Period | 11/07/22 → 15/07/22 |
Bibliographical note
Publisher Copyright:© 2022 ACM.
Funding
We thank the reviewers for their comments. This work was supported in part by a grant from Google.
Funders | Funder number |
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Keywords
- dialogue retrieval
- sentence retrieval