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Syntax-Informed Interactive Model for Comprehensive Aspect-Based Sentiment Analysis

arXiv 2312.03739 ↗First posted 28 Nov 2023cs.CLcited by 0

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Abstract (arXiv)

Aspect-based sentiment analysis (ABSA), a nuanced task in text analysis, seeks to discern sentiment orientation linked to specific aspect terms in text. Traditional approaches often overlook or inadequately model the explicit syntactic structures of sentences, crucial for effective aspect term identification and sentiment determination. Addressing this gap, we introduce an innovative model: Syntactic Dependency Enhanced Multi-Task Interaction Architecture (SDEMTIA) for comprehensive ABSA. Our approach innovatively exploits syntactic knowledge (dependency relations and types) using a specialized Syntactic Dependency Embedded Interactive Network (SDEIN). We also incorporate a novel and efficient message-passing mechanism within a multi-task learning framework to bolster learning efficacy. Our extensive experiments on benchmark datasets showcase our model's superiority, significantly surpassing existing methods. Additionally, incorporating BERT as an auxiliary feature extractor further enhances our model's performance.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 21 of its 69 references that are in the map. First posted on arXiv 28 Nov 2023.

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References · 21

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2019BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment Analysiscited by 176
  3. 2020Relational Graph Attention Network for Aspect-based Sentiment Analysiscited by 104
  4. 2017Interactive Attention Networks for Aspect-Level Sentiment Classificationcited by 91
  5. 2015Effective LSTMs for Target-Dependent Sentiment Classificationcited by 82
  6. 2019Adapt or Get Left Behind: Domain Adaptation through BERT Language Model Finetuning for Aspect-Target Sentiment Classificationcited by 63
  7. 2019Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networkscited by 63
  8. 2019Exploiting BERT for End-to-End Aspect-based Sentiment Analysiscited by 57
  9. 2019Open-Domain Targeted Sentiment Analysis via Span-Based Extraction and Classificationcited by 50
  10. 2019Attentional Encoder Network for Targeted Sentiment Classificationcited by 48
  11. 2018Transformation Networks for Target-Oriented Sentiment Classificationcited by 47
  12. 2023LasUIE: Unifying Information Extraction with Latent Adaptive Structure-aware Generative Language Modelcited by 43
9 more
  1. 2018Double Embeddings and CNN-based Sequence Labeling for Aspect Extractioncited by 42
  2. 2019Syntax-Aware Aspect Level Sentiment Classification with Graph Attention Networkscited by 40
  3. 2021Mastering the Explicit Opinion-role Interaction: Syntax-aided Neural Transition System for Unified Opinion Role Labelingcited by 25
  4. 2018Exploiting Document Knowledge for Aspect-level Sentiment Classificationcited by 19
  5. 2022OneEE: A One-Stage Framework for Fast Overlapping and Nested Event Extractioncited by 18
  6. 2019DOER: Dual Cross-Shared RNN for Aspect Term-Polarity Co-Extractioncited by 17
  7. 2018Left-Center-Right Separated Neural Network for Aspect-based Sentiment Analysis with Rotatory Attentioncited by 10
  8. 2019Selective Attention Based Graph Convolutional Networks for Aspect-Level Sentiment Classificationcited by 4
  9. 2023TKDP: Threefold Knowledge-enriched Deep Prompt Tuning for Few-shot Named Entity Recognitioncited by 2

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