Opinion Summarization
35 papers with code • 0 benchmarks • 0 datasets
The task of generating a summary of user opinions from reviews (and question-answers, etc)
Benchmarks
These leaderboards are used to track progress in Opinion Summarization
Most implemented papers
Unsupervised Opinion Summarization as Copycat-Review Generation
ixlan/CopyCat-abstractive-opinion-summarizer
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ACL 2020
At test time, when generating summaries, we force the novelty to be minimal, and produce a text reflecting consensus opinions.
Summarizing Opinions: Aspect Extraction Meets Sentiment Prediction and They Are Both Weakly Supervised
stangelid/oposum
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EMNLP 2018
We present a neural framework for opinion summarization from online product reviews which is knowledge-lean and only requires light supervision (e. g., in the form of product domain labels and user-provided ratings).
Extractive Opinion Summarization in Quantized Transformer Spaces
stangelid/qt
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We present the Quantized Transformer (QT), an unsupervised system for extractive opinion summarization.
Target-oriented Opinion Words Extraction with Target-fused Neural Sequence Labeling
In this paper, we propose a novel sequence labeling subtask for ABSA named TOWE (Target-oriented Opinion Words Extraction), which aims at extracting the corresponding opinion words for a given opinion target.
Informative and Controllable Opinion Summarization
rktamplayo/PlanSum
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EACL 2021
Opinion summarization is the task of automatically generating summaries for a set of reviews about a specific target (e. g., a movie or a product).
Weakly-Supervised Opinion Summarization by Leveraging External Information
Opinion summarization from online product reviews is a challenging task, which involves identifying opinions related to various aspects of the product being reviewed.
Unsupervised Opinion Summarization with Noising and Denoising
rktamplayo/DenoiseSum
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ACL 2020
We create a synthetic dataset from a corpus of user reviews by sampling a review, pretending it is a summary, and generating noisy versions thereof which we treat as pseudo-review input.
Few-Shot Learning for Opinion Summarization
In this work, we show that even a handful of summaries is sufficient to bootstrap generation of the summary text with all expected properties, such as writing style, informativeness, fluency, and sentiment preservation.
OpinionDigest: A Simple Framework for Opinion Summarization
megagonlabs/opiniondigest
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ACL 2020
The framework uses an Aspect-based Sentiment Analysis model to extract opinion phrases from reviews, and trains a Transformer model to reconstruct the original reviews from these extractions.
Read what you need: Controllable Aspect-based Opinion Summarization of Tourist Reviews
Manually extracting relevant aspects and opinions from large volumes of user-generated text is a time-consuming process.
