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View all- Loska APaszkowski WWaszkowski R(2024)The Scenario Approach to the Concept of Maintenance of Technical Systems of Urban EngineeringAdvances in Manufacturing IV10.1007/978-3-031-56444-4_7(84-97)Online publication date: 30-Mar-2024
Taxonomy of Abstractive Dialogue Summarization: Scenarios, Approaches, and Future Directions
Authors: 
Qi Jia, Yizhu Liu, Siyu Ren, Kenny Q. ZhuAuthors Info & Claims
Qi Jia, Yizhu Liu, Siyu Ren, Kenny Q. ZhuAuthors Info & ClaimsArticle No.: 67, Pages 1 - 38
Abstract
Abstractive dialogue summarization generates a concise and fluent summary covering the salient information in a dialogue among two or more interlocutors. It has attracted significant attention in recent years based on the massive emergence of social communication platforms and an urgent requirement for efficient dialogue information understanding and digestion. Different from news or articles in traditional document summarization, dialogues bring unique characteristics and additional challenges, including different language styles and formats, scattered information, flexible discourse structures, and unclear topic boundaries. This survey provides a comprehensive investigation of existing work for abstractive dialogue summarization from scenarios, approaches to evaluations. It categorizes the task into two broad categories according to the type of input dialogues, i.e., open-domain and task-oriented, and presents a taxonomy of existing techniques in three directions, namely, injecting dialogue features, designing auxiliary training tasks, and using additional data. A list of datasets under different scenarios and widely accepted evaluation metrics are summarized for completeness. After that, the trends of scenarios and techniques are summarized, together with deep insights into correlations between extensively exploited features and different scenarios. Based on these analyses, we recommend future directions, including more controlled and complicated scenarios, technical innovations and comparisons, publicly available datasets in special domains, and so on.
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Publication History
Published: 05 October 2023
Online AM: 07 September 2023
Accepted: 22 August 2023
Revised: 30 July 2023
Received: 30 January 2022
Published in CSUR Volume 56, Issue 3
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