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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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 31–40 of 92 papers

Title	Date	Tasks	Status	Hype	Score
Does local pruning offer task-specific models to learn effectively ?	Sep 1, 2021	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	0	5
An Aspect Extraction Framework using Different Embedding Types, Learning Models, and Dependency Structure	Mar 5, 2025	Aspect-Based Sentiment AnalysisAspect Extraction	CodeCode Available	0	5
Hyperbolic Disentangled Representation for Fine-Grained Aspect Extraction	Dec 16, 2021	Aspect Extraction	CodeCode Available	0	5
Improving Aspect Extraction based on Rules through Deep Syntax-Semantics Communication	Nov 16, 2021	Aspect ExtractionTerm Extraction	CodeCode Available	0	5
Dataset and Baseline for Automatic Student Feedback Analysis	Jun 1, 2022	Aspect ExtractionSentence	—Unverified	0	0
Aspect On: an Interactive Solution for Post-Editing the Aspect Extraction based on Online Learning	May 1, 2020	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified	0	0
Cross-domain aspect extraction for sentiment analysis: a transductive learning approach	Oct 21, 2018	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified	0	0
Aspect Extraction with Automated Prior Knowledge Learning	Jun 1, 2014	Aspect ExtractionSentiment Analysis	—Unverified	0	0
Aspect and Sentiment Aware Abstractive Review Summarization	Aug 1, 2018	Abstractive Text SummarizationAspect Extraction	—Unverified	0	0
Coupling Global and Local Context for Unsupervised Aspect Extraction	Nov 1, 2019	Aspect ExtractionSentence	—Unverified	0	0

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All datasets SemEval-2014 Task-4 SemEval 2015 Task 12 SemEval 2014 Task 4 Sub Task 1 SemEval 2016 Task 5 Sub Task 1 Slot 2 YASO - YELP

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	InstructABSA	Laptop (F1)	92.3	—	Unverified
2	ACE	Laptop (F1)	87.4	—	Unverified
3	PH-SUM	Laptop (F1)	86.09	—	Unverified
4	BAT	Laptop (F1)	85.57	—	Unverified
5	DE-CNN	Restaurant (F1)	85.2	—	Unverified
6	Wei et al. (2020)	Laptop (F1)	82.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ACE	Restaurant (F1)	80.3	—	Unverified
2	Wei et al. (2020)	Restaurant (F1)	72.7	—	Unverified
3	DE-CNN	Restaurant (F1)	68.28	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DE-CNN	Laptop (F1)	81.59	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DE-CNN	Restaurant (F1)	74.37	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RACL - Laptops	F1	23	—	Unverified