Aspect Extraction
32 papers with code • 6 benchmarks • 4 datasets
Aspect extraction is the task of identifying and extracting terms relevant for opinion mining and sentiment analysis, for example terms for product attributes or features.
Benchmarks
These leaderboards are used to track progress in Aspect Extraction
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SemEval-2014 Task-4
Latest papers
YASO: A Targeted Sentiment Analysis Evaluation Dataset for Open-Domain Reviews
Current TSA evaluation in a cross-domain setup is restricted to the small set of review domains available in existing datasets.
Joint Aspect Extraction and Sentiment Analysis with Directional Graph Convolutional Networks
cuhksz-nlp/dgsa
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COLING 2020
End-to-end aspect-based sentiment analysis (EASA) consists of two sub-tasks: the first extracts the aspect terms in a sentence and the second predicts the sentiment polarities for such terms.
Improving BERT Performance for Aspect-Based Sentiment Analysis
IMPLabUniPr/BERT-for-ABSA
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ICNLSP 2021
Aspect-Based Sentiment Analysis (ABSA) studies the consumer opinion on the market products.
Automated Concatenation of Embeddings for Structured Prediction
Pretrained contextualized embeddings are powerful word representations for structured prediction tasks.
Simple Unsupervised Similarity-Based Aspect Extraction
In the context of sentiment analysis, there has been growing interest in performing a finer granularity analysis focusing on the specific aspects of the entities being evaluated.
Modelling Context and Syntactical Features for Aspect-based Sentiment Analysis
HieuPhan33/LCFS-BERT
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ACL 2020
This increases the accuracy of the aspect sentiment classifier.
Jointly Modeling Aspect and Sentiment with Dynamic Heterogeneous Graph Neural Networks
Target-Based Sentiment Analysis aims to detect the opinion aspects (aspect extraction) and the sentiment polarities (sentiment detection) towards them.
Structure-Level Knowledge Distillation For Multilingual Sequence Labeling
Alibaba-NLP/MultilangStructureKD
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ACL 2020
Multilingual sequence labeling is a task of predicting label sequences using a single unified model for multiple languages.
Adversarial Training for Aspect-Based Sentiment Analysis with BERT
IMPLabUniPr/Adversarial-Training-for-ABSA
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In this work, we apply adversarial training, which was put forward by Goodfellow et al. (2014), to the post-trained BERT (BERT-PT) language model proposed by Xu et al. (2019) on the two major tasks of Aspect Extraction and Aspect Sentiment Classification in sentiment analysis.
Multilingual aspect clustering for sentiment analysis
In this article, we address the novel task of multilingual aspect clustering, which aims at grouping semantically related aspects extracted from reviews written in several languages.
