Papers with extractive summarization methods
Comprehensive Abstractive Comment Summarization with Dynamic Clustering and Chain of Thought (2024.findings-acl)
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| Challenge: | Recent work on news comment summarization has focused on extractive methods within constraints. |
| Approach: | They propose an enhanced fast clustering algorithm that maintains a dynamic similarity threshold to ensure high density of each comment cluster being built. |
| Outcome: | The proposed method improves the baseline methods and the test suite on real-world news comments. |
Facet-Aware Evaluation for Extractive Summarization (2020.acl-main)
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| Challenge: | lexical overlap is a common evaluation metric for extractive summarization, but recent studies reveal its limitations. |
| Approach: | They propose a facet-aware evaluation setup for better assessment of information coverage in extractive summaries. |
| Outcome: | The proposed evaluation setup improves human correlation with extractive summarization datasets and improves comparative analysis. |
TWEETSUM: Event oriented Social Summarization Dataset (2020.coling-main)
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| Challenge: | Developing social summarization systems is becoming more and more critical . but, the publicly available and high-quality large scale social summaries are rare . |
| Approach: | They propose to build a social summarization dataset using twitter's hot events . they collect user relations, hashtags and user profiles to evaluate their summarizing methods . |
| Outcome: | The proposed dataset is based on a dataset from twitter with 12 real world hot events with 44,034 tweets and 11,240 users. |
TSix: A Human-involved-creation Dataset for Tweet Summarization (L18-1)
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| Challenge: | a new dataset for tweet summarization is available for free. |
| Approach: | They propose a dataset for tweet summarization that uses human annotations to evaluate extractive summarizing methods. |
| Outcome: | The proposed dataset includes six events collected from Twitter . human-annotated gold-standard references facilitate evaluation, the study shows . |
Annotation and Analysis of Extractive Summaries for the Kyutech Corpus (L18-1)
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| Challenge: | Summarization of multi-party conversation requires corpora to analyze characteristics of conversations and construct a method for summary generation. |
| Approach: | They propose to annotate a Japanese conversation corpus for a decision-making task . they compare extractive summarization methods with the annotated extractive summary . |
| Outcome: | The proposed corpus is the first annotated for conversation summarization tasks and freely available to anyone. |