Unsupervised Aspect-Based Multi-Document Abstractive Summarization
User-generated reviews of products or services provide valuable information to customers. However, it is often impossible to read each of the potentially thousands of reviews: it would therefore save valuable time to provide short summaries of their contents. We address opinion summarization, a multi-document summarization task, with an unsupervised abstractive summarization neural system. Our system is based on (i) a language model that is meant to encode reviews to a vector space, and to generate fluent sentences from the same vector space (ii) a clustering step that groups together reviews about the same aspects and allows the system to generate summary sentences focused on these aspects. Our experiments on the Oposum dataset empirically show the importance of the clustering step.
Code (0)
등록된 구현이 없습니다.
Tasks
Abstractive Text SummarizationClusteringDocument SummarizationLanguage ModelingLanguage ModellingMulti-Document SummarizationOpinion SummarizationSimilar Papers 제목 키워드 기반
Unsupervised Abstractive Summarization of Bengali Text Documents
Abstractive summarization systems generally rely on large collections of document-summary pairs. However, the performance of abstractive systems remains a challenge due to the unavailability of parallel data for low-reso…
Abstractive Text SummarizationExtractive SummarizationLanguage ModelingLanguage Modelling+2Inducing Document Structure for Aspect-based Summarization
Automatic summarization is typically treated as a 1-to-1 mapping from document to summary. Documents such as news articles, however, are structured and often cover multiple topics or aspects; and readers may be intereste…
Abstractive Text SummarizationArticlesAn Unsupervised Masking Objective for Abstractive Multi-Document News Summarization
We show that a simple unsupervised masking objective can approach near supervised performance on abstractive multi-document news summarization. Our method trains a state-of-the-art neural summarization model to predict t…
Extractive SummarizationNews SummarizationAbstractive Unsupervised Multi-Document Summarization using Paraphrastic Sentence Fusion
In this work, we aim at developing an unsupervised abstractive summarization system in the multi-document setting. We design a paraphrastic sentence fusion model which jointly performs sentence fusion and paraphrasing us…
Abstractive Text SummarizationDocument SummarizationMachine TranslationMulti-Document Summarization+5Absformer: Transformer-based Model for Unsupervised Multi-Document Abstractive Summarization
Multi-document summarization (MDS) refers to the task of summarizing the text in multiple documents into a concise summary. The generated summary can save the time of reading many documents by providing the important con…
Abstractive Text SummarizationDecoderDocument SummarizationLanguage Modeling+4