Papers Multi-Domain Sentiment Classification
“Multi-Domain Sentiment Classification” 태그가 달린 논문 7편 · 필터 해제
Dynamic Domain Information Modulation Algorithm for Multi-domain Sentiment Analysis
Multi-domain sentiment classification aims to mitigate poor performance models due to the scarcity of labeled data in a single domain, by utilizing data labeled from various domains. A series of models that jointly train…
Classificationdomain classificationHyperparameter OptimizationMulti-Domain Sentiment Classification+2Is ChatGPT a Good Sentiment Analyzer? A Preliminary Study
Recently, ChatGPT has drawn great attention from both the research community and the public. We are particularly interested in whether it can serve as a universal sentiment analyzer. To this end, in this work, we provide…
Aspect-Based Sentiment Analysis (ABSA)Emotion Cause ExtractionEmotion-Cause Pair ExtractionExtract aspect-polarity tuple+2Learn2Weight: Parameter Adaptation against Similar-domain Adversarial Attacks
Recent work in black-box adversarial attacks for NLP systems has attracted much attention. Prior black-box attacks assume that attackers can observe output labels from target models based on selected inputs. In this work…
Adversarial AttackDomain AdaptationMeta-LearningMulti-Domain Sentiment Classification+2Learning to Share by Masking the Non-shared for Multi-domain Sentiment Classification
Multi-domain sentiment classification deals with the scenario where labeled data exists for multiple domains but insufficient for training effective sentiment classifiers that work across domains. Thus, fully exploiting …
General ClassificationMulti-Domain Sentiment ClassificationSentenceSentiment Analysis+1Learn2Weight: Weights Transfer Defense against Similar-domain Adversarial Attacks
Recent work in black-box adversarial attacks for NLP systems has attracted attention. Prior black-box attacks assume that attackers can observe output labels from target models based on selected inputs. In this work, ins…
Adversarial AttackDomain AdaptationMulti-Domain Sentiment ClassificationSentiment Analysis+1Dual Adversarial Co-Learning for Multi-Domain Text Classification
In this paper we propose a novel dual adversarial co-learning approach for multi-domain text classification (MDTC). The approach learns shared-private networks for feature extraction and deploys dual adversarial regulari…
ClassificationGeneral ClassificationMulti-Domain Sentiment ClassificationSentiment Analysis+3Learning Domain Representation for Multi-Domain Sentiment Classification
Training data for sentiment analysis are abundant in multiple domains, yet scarce for other domains. It is useful to leveraging data available for all existing domains to enhance performance on different domains. We inve…
ClassificationGeneral ClassificationMulti-Domain Sentiment ClassificationMulti-Task Learning+2