Papers Unsupervised Opinion Summarization
“Unsupervised Opinion Summarization” 태그가 달린 논문 9편 · 필터 해제
Automatically Evaluating Opinion Prevalence in Opinion Summarization
When faced with a large number of product reviews, it is not clear that a human can remember all of them and weight opinions representatively to write a good reference summary. We propose an automatic metric to test the …
Opinion SummarizationUnsupervised Opinion SummarizationAttributable and Scalable Opinion Summarization
We propose a method for unsupervised opinion summarization that encodes sentences from customer reviews into a hierarchical discrete latent space, then identifies common opinions based on the frequency of their encodings…
Opinion SummarizationUnsupervised Opinion SummarizationSimple Yet Effective Synthetic Dataset Construction for Unsupervised Opinion Summarization
Opinion summarization provides an important solution for summarizing opinions expressed among a large number of reviews. However, generating aspect-specific and general summaries is challenging due to the lack of annotat…
Natural Language InferenceOpinion SummarizationUnsupervised Opinion SummarizationUnsupervised Opinion Summarization Using Approximate Geodesics
Opinion summarization is the task of creating summaries capturing popular opinions from user reviews. In this paper, we introduce Geodesic Summarizer (GeoSumm), a novel system to perform unsupervised extractive opinion s…
DecoderDictionary LearningOpinion SummarizationRepresentation Learning+1OrderSum: Reading Order-Aware Unsupervised Opinion Summarization
Opinion summarization aims to create a concise summary reflecting subjective information conveyed by multiple user reviews about the same product. To avoid the high expense of curating golden summaries for training, many…
Opinion SummarizationUnsupervised Opinion SummarizationConvex Aggregation for Opinion Summarization
Recent advances in text autoencoders have significantly improved the quality of the latent space, which enables models to generate grammatical and consistent text from aggregated latent vectors. As a successful applicati…
Opinion SummarizationUnsupervised Opinion SummarizationUnsupervised Opinion Summarization with Content Planning
The recent success of deep learning techniques for abstractive summarization is predicated on the availability of large-scale datasets. When summarizing reviews (e.g., for products or movies), such training data is neith…
Abstractive Text SummarizationOpinion SummarizationUnsupervised Opinion SummarizationUnsupervised Opinion Summarization with Noising and Denoising
The supervised training of high-capacity models on large datasets containing hundreds of thousands of document-summary pairs is critical to the recent success of deep learning techniques for abstractive summarization. Un…
Abstractive Text SummarizationDenoisingOpinion SummarizationUnsupervised Opinion SummarizationUnsupervised Opinion Summarization as Copycat-Review Generation
Opinion summarization is the task of automatically creating summaries that reflect subjective information expressed in multiple documents, such as product reviews. While the majority of previous work has focused on the e…
Abstractive Text SummarizationOpinion SummarizationReview GenerationUnsupervised Opinion Summarization