short-paper

Summarizing and Exploring Tabular Data in Conversational Search

Authors:

Shuo Zhang,

Zhuyun Dai,

Krisztian Balog,

Jamie CallanAuthors Info & Claims

SIGIR '20: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval

Pages 1537 - 1540

https://doi.org/10.1145/3397271.3401205

Published: 25 July 2020 Publication History

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Abstract

Tabular data provide answers to a significant portion of search queries. However, reciting an entire result table is impractical in conversational search systems. We propose to generate natural language summaries as answers to describe the complex information contained in a table. Through crowdsourcing experiments, we build a new conversation-oriented, open-domain table summarization dataset. It includes annotated table summaries, which not only answer questions but also help people explore other information in the table. We utilize this dataset to develop automatic table summarization systems as SOTA baselines. Based on the experimental results, we identify challenges and point out future research directions that this resource will support.

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Tabular data provide answers to a significant portion of search queries. However, reciting an entire result table is impractical in conversational search systems.\r\nWe propose to generate natural language summaries as answers to describe the complex information contained in a table.\r\nThrough crowdsourcing experiments, we build a new conversation-oriented, open-domain table summarization dataset. It includes annotated table summaries, which not only answer questions but also help people explore other information in the table. \r\nWe utilize this dataset to develop automatic table summarization systems as SOTA baselines. \r\nBased on the experimental results, we identify challenges and point out future research directions that this resource will support.

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References

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Cited By

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Huang JChen HYu FLu W(2024)From Detection to Application: Recent Advances in Understanding Scientific Tables and FiguresACM Computing Surveys10.1145/365728556:10(1-39)Online publication date: 22-Jun-2024
https://dl.acm.org/doi/10.1145/3657285
Li PHe YYashar DCui WGe SZhang HRifinski Fainman DZhang DChaudhuri S(2024)Table-GPT: Table Fine-tuned GPT for Diverse Table TasksProceedings of the ACM on Management of Data10.1145/36549792:3(1-28)Online publication date: 30-May-2024
https://dl.acm.org/doi/10.1145/3654979
Chen XLi MGao SCheng XZhu QYan RGao XZhang XHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)Flexible and Adaptable Summarization via Expertise SeparationProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657789(2018-2027)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657789
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Index Terms

Summarizing and Exploring Tabular Data in Conversational Search
1. Information systems
  1. Information retrieval
    1. Specialized information retrieval
      1. Environment-specific retrieval

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Published In

SIGIR '20: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval

July 2020

2548 pages

ISBN:9781450380164

DOI:10.1145/3397271

General Chairs:
Jimmy Huang
York University, Canada
,
Yi Chang
Jilin University, China
,
Xueqi Cheng
Chinese Academy of Sciences, China
,
Program Chairs:
Jaap Kamps
University of Amsterdam, Netherlands
,
Vanessa Murdock
Amazon, U.S.A.
,
Ji-Rong Wen
Renmin University of China, China
,
Yiqun Liu
Tsinghua University, China

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 July 2020

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Funding Sources

National Science Foundation (NSF) grant IIS-1815528

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SIGIR '20

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SIGIR

SIGIR '20: The 43rd International ACM SIGIR conference on research and development in Information Retrieval

July 25 - 30, 2020

Virtual Event, China

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Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Cited By

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Huang JChen HYu FLu W(2024)From Detection to Application: Recent Advances in Understanding Scientific Tables and FiguresACM Computing Surveys10.1145/365728556:10(1-39)Online publication date: 22-Jun-2024
https://dl.acm.org/doi/10.1145/3657285
Li PHe YYashar DCui WGe SZhang HRifinski Fainman DZhang DChaudhuri S(2024)Table-GPT: Table Fine-tuned GPT for Diverse Table TasksProceedings of the ACM on Management of Data10.1145/36549792:3(1-28)Online publication date: 30-May-2024
https://dl.acm.org/doi/10.1145/3654979
Chen XLi MGao SCheng XZhu QYan RGao XZhang XHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)Flexible and Adaptable Summarization via Expertise SeparationProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657789(2018-2027)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657789
Ghosh SGhosh SShah CKlein MBen-David AJäschke RKelly M(2024)Toward Connecting Speech Acts and Search Actions in Conversational Search TasksProceedings of the 2023 ACM/IEEE Joint Conference on Digital Libraries10.1109/JCDL57899.2023.00027(119-131)Online publication date: 26-Jun-2024
https://dl.acm.org/doi/10.1109/JCDL57899.2023.00027
Mo XXiang YPan YHou YLuo P(2024)MGCoT: Multi-Grained Contextual Transformer for table-based text generationExpert Systems with Applications10.1016/j.eswa.2024.123742250(123742)Online publication date: Sep-2024
https://doi.org/10.1016/j.eswa.2024.123742
Chen QGao XGuo XWang S(2023)Multi-head attention based candidate segment selection in QA over hybrid dataIntelligent Data Analysis10.3233/IDA-22703227:6(1839-1852)Online publication date: 20-Nov-2023
https://doi.org/10.3233/IDA-227032
Shigarov A(2022)Table understanding: Problem overviewWIREs Data Mining and Knowledge Discovery10.1002/widm.148213:1Online publication date: 21-Nov-2022
https://doi.org/10.1002/widm.1482
Li DRen ZRen PChen ZFan MMa Jde Rijke MDiaz FShah CSuel TCastells PJones RSakai T(2021)Semi-Supervised Variational Reasoning for Medical Dialogue GenerationProceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3404835.3462921(544-554)Online publication date: 11-Jul-2021
https://dl.acm.org/doi/10.1145/3404835.3462921
Deldjoo YTrippas JZamani HDiaz FShah CSuel TCastells PJones RSakai T(2021)Towards Multi-Modal Conversational Information SeekingProceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3404835.3462806(1577-1587)Online publication date: 11-Jul-2021
https://dl.acm.org/doi/10.1145/3404835.3462806
Algergawy AHamed HKönig-Ries B(2021)Towards Scientific Data Synthesis Using Deep Learning and Semantic WebThe Semantic Web: ESWC 2021 Satellite Events10.1007/978-3-030-80418-3_10(54-59)Online publication date: 6-Jun-2021
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