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Aspect Extraction

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.

Papers

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Showing 26–50 of 92 papers

TitleStatusHype
Enhancing Review Comprehension with Domain-Specific Commonsense—0
Ensemble Creation via Anchored Regularization for Unsupervised Aspect Extraction—0
Exploiting Domain Knowledge in Aspect Extraction—0
From Annotation to Adaptation: Metrics, Synthetic Data, and Aspect Extraction for Aspect-Based Sentiment Analysis with Large Language Models—0
Implicit and Explicit Aspect Extraction in Financial Microblogs—0
Zero-Shot Aspect-Based Sentiment Analysis—0
A Framework of Customer Review Analysis Using the Aspect-Based Opinion Mining Approach—0
A Rule-Based Approach to Aspect Extraction from Product Reviews—0
Aspect and Sentiment Aware Abstractive Review Summarization—0
Aspect-based Opinion Summarization with Convolutional Neural Networks—0
Aspect Extraction and Sentiment Classification of Mobile Apps using App-Store Reviews—0
Aspect Extraction from Product Reviews Using Category Hierarchy Information—0
Aspect Extraction through Semi-Supervised Modeling—0
Aspect Extraction Using Coreference Resolution and Unsupervised Filtering—0
Aspect Extraction with Automated Prior Knowledge Learning—0
Aspect On: an Interactive Solution for Post-Editing the Aspect Extraction based on Online Learning—0
Aspect Oriented Suggestion Extraction from Online Reviews—0
AspeRa: Aspect-Based Rating Prediction Based on User Reviews—0
A Weak Supervision Approach for Few-Shot Aspect Based Sentiment—0
Basic tasks of sentiment analysis—0
Can a Humanoid Robot be part of the Organizational Workforce? A User Study Leveraging Sentiment Analysis—0
Opinion aspect extraction in Dutch childrens diary entries—0
PL-FGSA: A Prompt Learning Framework for Fine-Grained Sentiment Analysis Based on MindSpore—0
Polarity in the Classroom: A Case Study Leveraging Peer Sentiment Toward Scalable Assessment—0
Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations—0
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All datasetsSemEval-2014 Task-4SemEval 2015 Task 12SemEval 2014 Task 4 Sub Task 1SemEval 2016 Task 5 Sub Task 1 Slot 2YASO - YELP

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1InstructABSALaptop (F1)92.3—Unverified
2ACELaptop (F1)87.4—Unverified
3PH-SUMLaptop (F1)86.09—Unverified
4BATLaptop (F1)85.57—Unverified
5DE-CNNRestaurant (F1)85.2—Unverified
6Wei et al. (2020)Laptop (F1)82.7—Unverified
#ModelMetricClaimedVerifiedStatus
1ACERestaurant (F1)80.3—Unverified
2Wei et al. (2020)Restaurant (F1)72.7—Unverified
3DE-CNNRestaurant (F1)68.28—Unverified
#ModelMetricClaimedVerifiedStatus
1DE-CNNLaptop (F1)81.59—Unverified
#ModelMetricClaimedVerifiedStatus
1DE-CNNRestaurant (F1)74.37—Unverified
#ModelMetricClaimedVerifiedStatus
1RACL - LaptopsF123—Unverified