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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 1–10 of 92 papers

Title	Date	Tasks	Status	Hype
Cross-Domain Aspect Extraction using Transformers Augmented with Knowledge Graphs	Oct 18, 2022	Aspect ExtractionKnowledge Graphs	CodeCode Available	4
InstructABSA: Instruction Learning for Aspect Based Sentiment Analysis	Feb 16, 2023	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	1
Adversarial Training for Aspect-Based Sentiment Analysis with BERT	Jan 30, 2020	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	1
BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment Analysis	Apr 3, 2019	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	1
DILBERT: Customized Pre-Training for Domain Adaptation with Category Shift, with an Application to Aspect Extraction	Nov 1, 2021	Aspect ExtractionDomain Adaptation	CodeCode Available	1
Improving BERT Performance for Aspect-Based Sentiment Analysis	Oct 22, 2020	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	1
Automatic Controllable Product Copywriting for E-Commerce	Jun 21, 2022	Aspect ExtractionLanguage Modeling	CodeCode Available	1
Automated Concatenation of Embeddings for Structured Prediction	Oct 10, 2020	Aspect ExtractionChunking	CodeCode Available	1
DILBERT: Customized Pre-Training for Domain Adaptation withCategory Shift, with an Application to Aspect Extraction	Sep 1, 2021	Aspect ExtractionDomain Adaptation	CodeCode Available	1
Joint Aspect Extraction and Sentiment Analysis with Directional Graph Convolutional Networks	Dec 1, 2020	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	1

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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