A Dataset for Sentence Retrieval for Open-Ended Dialogues

Itay Harel, Hagai Taitelbaum, Idan Szpektor, Oren Kurland

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

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 languageEnglish
Title of host publicationSIGIR 2022 - Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
PublisherAssociation for Computing Machinery, Inc
Pages2960-2969
Number of pages10
ISBN (Electronic)9781450387323
DOIs
StatePublished - 6 Jul 2022
Externally publishedYes
Event45th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2022 - Madrid, Spain
Duration: 11 Jul 202215 Jul 2022

Publication series

NameSIGIR 2022 - Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

Conference

Conference45th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2022
Country/TerritorySpain
CityMadrid
Period11/07/2215/07/22

Bibliographical note

Publisher Copyright:
© 2022 ACM.

Keywords

  • dialogue retrieval
  • sentence retrieval

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