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Target-Aspect-Sentiment Joint Detection for Aspect-Based Sentiment Analysis

AAAI 2020 · Detection and segmentation › CNN features · approach: Arbitrary-shape scene text detection · 174 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
joint training of yes/no classification and target sequence labeling (vs separate models) (ablation)TAS-BERT-SW-BIO-CRF · Res16 TASDmicro-F1: 62.42 -> 65.89Helped
joint training vs separate (ablation)TAS-BERT-SW-TO · Res15 TASDmicro-F1: 53.92 -> 58.09Helped
joint training vs separate (ablation)TAS-BERT-SW-BIO-CRF · Res16 implicit-target opinionsmicro-F1: 44.83 -> 50.59Helped
Split Word handling of unknown words instead of Longest Prefix Match (ablation)TAS-BERT-BIO-CRF · Res15 TASDmicro-F1: 54.76 -> 57.51Helped
TO tagging + softmax instead of BIO + CRF (ablation)TAS-BERT-SW · Res16 TDmicro-F1: 81.37 -> 78.10Hurt
TO tagging + softmax instead of BIO + CRF (ablation)TAS-BERT-SW · Res15 ADmicro-F1: 76.34 -> 76.40Helped
joint target-aspect-sentiment detection with BERTASD baseline BERT-pair-NLI-B · Res15 ASDmicro-F1: 63.67 -> 70.42Helped
joint detection handling implicit targetsDOER · Res16 TSDmicro-F1: 65.91 -> 75.68Helped

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