SOTAVerified

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

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Showing 1–10 of 92 papers

TitleStatusHype
PL-FGSA: A Prompt Learning Framework for Fine-Grained Sentiment Analysis Based on MindSpore—0
From Annotation to Adaptation: Metrics, Synthetic Data, and Aspect Extraction for Aspect-Based Sentiment Analysis with Large Language Models—0
An Aspect Extraction Framework using Different Embedding Types, Learning Models, and Dependency StructureCode0
Visual Zero-Shot E-Commerce Product Attribute Value Extraction—0
Learning to Extract Cross-Domain Aspects and Understanding Sentiments Using Large Language Models—0
Instruct-DeBERTa: A Hybrid Approach for Aspect-based Sentiment Analysis on Textual Reviews—0
SEOpinion: Summarization and Exploration Opinion of E-Commerce Websites—0
Deep Learning Brasil at ABSAPT 2022: Portuguese Transformer Ensemble ApproachesCode0
Automatic Aspect Extraction from Scientific TextsCode0
A Wide Evaluation of ChatGPT on Affective Computing TasksCode0
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All datasetsSemEval-2014 Task-4SemEval 2015 Task 12SemEval 2014 Task 4 Sub Task 1SemEval 2016 Task 5 Sub Task 1 Slot 2YASO - YELP

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DE-CNNRestaurant (F1)74.37—Unverified