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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
Polarity in the Classroom: A Case Study Leveraging Peer Sentiment Toward Scalable Assessment	Aug 2, 2021	Aspect ExtractionForm	—Unverified	0
Enhancing Aspect Extraction for Hindi	Aug 1, 2021	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified	0
YASO: A Targeted Sentiment Analysis Evaluation Dataset for Open-Domain Reviews	Dec 29, 2020	Aspect ExtractionSentiment Analysis	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
Label Correction Model for Aspect-based Sentiment Analysis	Dec 1, 2020	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified	0
Aspect Extraction Using Coreference Resolution and Unsupervised Filtering	Dec 1, 2020	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified	0
Unified Feature and Instance Based Domain Adaptation for Aspect-Based Sentiment Analysis	Nov 1, 2020	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified	0
Improving BERT Performance for Aspect-Based Sentiment Analysis	Oct 22, 2020	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	1
Automated Concatenation of Embeddings for Structured Prediction	Oct 10, 2020	Aspect ExtractionChunking	CodeCode Available	1
E-BERT: A Phrase and Product Knowledge Enhanced Language Model for E-commerce	Sep 7, 2020	Aspect ExtractionDenoising	—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