Aspect Extraction
30 papers with code • 11 benchmarks • 3 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 Sub Task 2
Most implemented papers
Knowing What, How and Why: A Near Complete Solution for Aspect-based Sentiment Analysis
In this paper, we introduce a new subtask under ABSA, named aspect sentiment triplet extraction (ASTE).
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.
An Unsupervised Neural Attention Model for Aspect Extraction
Unlike topic models which typically assume independently generated words, word embedding models encourage words that appear in similar contexts to be located close to each other in the embedding space.
Double Embeddings and CNN-based Sequence Labeling for Aspect Extraction
Unlike other highly sophisticated supervised deep learning models, this paper proposes a novel and yet simple CNN model employing two types of pre-trained embeddings for aspect extraction: general-purpose embeddings and domain-specific embeddings.
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).
Robust to Noise Models in Natural Language Processing Tasks
madrugado/robust-w2v
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ACL 2019
There are a lot of noise texts surrounding a person in modern life.
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.
Automated Concatenation of Embeddings for Structured Prediction
Pretrained contextualized embeddings are powerful word representations for structured prediction tasks.
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.
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.
