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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 61–70 of 92 papers

Title	Date	Tasks	Status	Hype
Unsupervised Neural Aspect Search with Related Terms Extraction	May 6, 2020	Aspect ExtractionTerm Extraction	—Unverified	0
Using Aspect Extraction Approaches to Generate Review Summaries and User Profiles	Apr 23, 2018	Aspect ExtractionReranking	—Unverified	0
Visual Zero-Shot E-Commerce Product Attribute Value Extraction	Feb 21, 2025	Aspect ExtractionAttribute	—Unverified	0
Weakly-supervised Domain Adaption for Aspect Extraction via Multi-level Interaction Transfer	Jun 16, 2020	Aspect ExtractionDomain Adaptation	—Unverified	0
Improving Aspect-Level Sentiment Analysis with Aspect Extraction	May 3, 2020	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified	0
Improving unsupervised neural aspect extraction for online discussions using out-of-domain classification	Jun 17, 2020	ArticlesAspect Extraction	—Unverified	0
INSIGHT-1 at SemEval-2016 Task 5: Deep Learning for Multilingual Aspect-based Sentiment Analysis	Sep 9, 2016	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified	0
Instruct-DeBERTa: A Hybrid Approach for Aspect-based Sentiment Analysis on Textual Reviews	Aug 23, 2024	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified	0
Label Correction Model for Aspect-based Sentiment Analysis	Dec 1, 2020	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified	0
Learning multilingual topics through aspect extraction from monolingual texts	Jan 1, 2019	Aspect ExtractionMultilingual Word Embeddings	—Unverified	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