Exploring Content Selection in Summarization of Novel Chapters
We present a new summarization task, generating summaries of novel chapters using summary/chapter pairs from online study guides. This is a harder task than the news summarization task, given the chapter length as well as the extreme paraphrasing and generalization found in the summaries. We focus on extractive summarization, which requires the creation of a gold-standard set of extractive summaries. We present a new metric for aligning reference summary sentences with chapter sentences to create gold extracts and also experiment with different alignment methods. Our experiments demonstrate significant improvement over prior alignment approaches for our task as shown through automatic metrics and a crowd-sourced pyramid analysis. We make our data collection scripts available at https://github.com/manestay/novel-chapter-dataset .
Code (1)
Tasks
Extractive SummarizationNews SummarizationSimilar Papers 제목 키워드 기반
Novel Chapter Abstractive Summarization using Spinal Tree Aware Sub-Sentential Content Selection
Summarizing novel chapters is a difficult task due to the input length and the fact that sentences that appear in the desired summaries draw content from multiple places throughout the chapter. We present a pipelined ext…
Abstractive Text SummarizationExtractive SummarizationNovel Chapter Abstractive Summarization using Spinal Tree Aware Sub-Sentential Content Selection
Summarizing novel chapters is a difficult task due to the length of the chapter to be summarized and the fact that summary sentences draw content from multiple sentences in the chapter. We present a pipelined extractive-…
Abstractive Text SummarizationCOLING 2022 Shared Task: LED Finteuning and Recursive Summary Generation for Automatic Summarization of Chapters from Novels
We present the results of the Workshop on Automatic Summarization for Creative Writing 2022 Shared Task on summarization of chapters from novels. In this task, we finetune a pretrained transformer model for long document…
16kDifferent approaches for identifying important concepts in probabilistic biomedical text summarization
Automatic text summarization tools help users in biomedical domain to acquire their intended information from various textual resources more efficiently. Some of the biomedical text summarization systems put the basis of…
feature selectionSentenceText SummarizationA Cascade Approach to Neural Abstractive Summarization with Content Selection and Fusion
We present an empirical study in favor of a cascade architecture to neural text summarization. Summarization practices vary widely but few other than news summarization can provide a sufficient amount of training data en…
Abstractive Text SummarizationNews SummarizationText GenerationText Summarization