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Related Papers
An NTU-Approach to Automatic Sentence Extraction for Summary Generation
Automatic summarization and information extraction are two important Internet services. MUC and SUMMAC play their appropriate roles in the next generation Internet. This paper focuses on the automatic summarization and …...
Improving Robust Domain Independent Summarization
We discuss those techniques which, in the opinion of the authors, are needed to support robust automatic summarization. Many of these methods are already incorporated in a multi-lingual summarization system, …...
Dependency-based Sentence Alignment for Multiple Document Summarization
In this paper, we describe a method of automatic sentence alignment for building extracts from ab- stracts in automatic summarization research. Our method is based on two steps. First, we …...
Kernel-based Approach for Automatic Evaluation of Natural Language Generation Technologies: Application to Automatic Summarization
In order to promote the study of auto- matic summarization and translation, we need an accurate automatic evaluation method that is close to human evalua- tion. In this paper, we …...
Significant Sentence Extraction by Euclidean Distance Based on Singular Value Decomposition
. This paper describes an automatic summarization approach that constructs a summary by extracting the significant sentences. The approach takes advantage of the cooccurrence relationships between terms only in the …...
Terminologie et paramètres expérimentaux pour l’évaluation des résumés automatiques [Terminology and experimental parameters for the evaluation of automatic summaries]
. In this paper, we first propose a terminology to be used in the French presentation of evaluation results of automatic summaries. In the second part of the paper, we …...
Understanding and Summarizing Answers in Community-Based Question Answering Services
Community-based question answering (cQA) services have accumulated millions of questions and their answers over time. In the process of accumulation, cQA ser- vices assume that questions always have unique best …...
Automatic Summarization Using Terminological and Semantic Resources
AbstractThis paper presents a new algorithm for automatic summarization of specialized texts combining terminological and semantic resources: a term extractor and an ontology. The term extractor provides the list of …...
On-line Summarization of Time-series Documents using a Graph-based Algorithm
As enormous amount of electronic documents on the Web have been increasing, the ne- cessity of automatic summarization has also been increasing to help people grasp the essen- tial points …...
What’s the Issue Here?: Task-based Evaluation of Reader Comment Summarization Systems
AbstractAutomatic summarization of reader comments in on-line news is an extremely challenging task and a capability for which there is a clear need. Work to date has focussed on producing …...
International Journal of Computational Linguistics & Chinese Language Processing, Volume 22, Number 1, June 2017
Due to the rapid-developed Internet and with the big data era coming, the automatic summarization research has been emerged a popular research topic. The aim of automatic summarization is in …...
Align then Summarize: Automatic Alignment Methods for Summarization Corpus Creation
AbstractSummarizing texts is not a straightforward task. Before even considering text summarization, one should determine what kind of summary is expected. How much should the information be compressed? Is it …...
Flight of the PEGASUS? Comparing Transformers on Few-shot and Zero-shot Multi-document Abstractive Summarization
AbstractRecent work has shown that pre-trained Transformers obtain remarkable performance on many natural language processing tasks including automatic summarization. However, most work has focused on (relatively) data-rich single-document summarization settings. …...
News Editorials: Towards Summarizing Long Argumentative Texts
AbstractThe automatic summarization of argumentative texts has hardly been explored. This paper takes a further step in this direction, targeting news editorials, i.e., opinionated articles with a well-defined argumentation structure. …...
Evaluating the Efficacy of Summarization Evaluation across Languages
While automatic summarization evaluation methods developed for English are routinely applied to other languages, this is the first at- tempt to systematically quantify their panlin- guistic efficacy. We take a …...
Optimizing Domain Specificity of Transformer-based Language Models for Extractive Summarization of Financial News Articles in Korean
Frequent usage of complex expressions with numbers and of the terms that require domain knowledge makes it more difficult to com- prehend and summarize financial news arti- cles than that …...
An Exploration of Post-Editing Effectiveness in Text Summarization
AbstractAutomatic summarization methods are efficient but can suffer from low quality. In comparison, manual summarization is expensive but produces higher quality. Can humans and AI collaborate to improve summarization performance? …...
Re-Examining System-Level Correlations of Automatic Summarization Evaluation Metrics
AbstractHow reliably an automatic summarization evaluation metric replicates human judgments of summary quality is quantified by system-level correlations. We identify two ways in which the definition of the system-level correlation …...
Element-aware Summarization with Large Language Models: Expert-aligned Evaluation and Chain-of-Thought Method
AbstractAutomatic summarization generates concise summaries that contain key ideas of source documents. As the most mainstream datasets for the news sub-domain, CNN/DailyMail and BBC XSum have been widely used for …...