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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 11–20 of 92 papers

Title	Date	Tasks	Status	Hype
Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations	Jun 2, 2023	Aspect ExtractionPrompt Learning	—Unverified	0
A Weak Supervision Approach for Few-Shot Aspect Based Sentiment	May 19, 2023	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified	0
Self-training through Classifier Disagreement for Cross-Domain Opinion Target Extraction	Feb 28, 2023	Aspect ExtractionDomain Adaptation	—Unverified	0
InstructABSA: Instruction Learning for Aspect Based Sentiment Analysis	Feb 16, 2023	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	1
A Framework of Customer Review Analysis Using the Aspect-Based Opinion Mining Approach	Dec 20, 2022	Aspect ExtractionOpinion Mining	—Unverified	0
UnifiedABSA: A Unified ABSA Framework Based on Multi-task Instruction Tuning	Nov 20, 2022	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified	0
Cross-Domain Aspect Extraction using Transformers Augmented with Knowledge Graphs	Oct 18, 2022	Aspect ExtractionKnowledge Graphs	CodeCode Available	4
Ensemble Creation via Anchored Regularization for Unsupervised Aspect Extraction	Oct 13, 2022	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified	0
A Hierarchical Interactive Network for Joint Span-based Aspect-Sentiment Analysis	Aug 24, 2022	Aspect ExtractionSentiment Analysis	CodeCode Available	0
SETSum: Summarization and Visualization of Student Evaluations of Teaching	Jul 8, 2022	Aspect ExtractionSentiment Analysis	CodeCode Available	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