A Dataset for Sentence Retrieval for Open-Ended Dialogues

Itay Harel, Hagai Taitelbaum, Idan Szpektor, Oren Kurland

פרסום מחקרי: פרק בספר / בדוח / בכנספרסום בספר כנסביקורת עמיתים

תקציר

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.

שפה מקוריתאנגלית
כותר פרסום המארחSIGIR 2022 - Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
עמודים2960-2969
מספר עמודים10
מסת"ב (אלקטרוני)9781450387323
מזהי עצם דיגיטלי (DOIs)
סטטוס פרסוםפורסם - 6 יולי 2022
אירוע45th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2022 - Madrid, ספרד
משך הזמן: 11 יולי 202215 יולי 2022

סדרות פרסומים

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

כנס

כנס45th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2022
מדינה/אזורספרד
עירMadrid
תקופה11/07/2215/07/22

ASJC Scopus subject areas

  • ???subjectarea.asjc.1700.1704???
  • ???subjectarea.asjc.1700.1710???
  • ???subjectarea.asjc.1700.1712???

פורמט ציטוט ביבליוגרפי