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Learning to Adapt Credible Knowledge in Cross-lingual Sentiment Analysis
TLDR
Cross-lingual sentiment analysis is a task of identifying sentiment polarities of texts in a low-resource language by using sentiment knowledge in a resource-abundant language. Expand
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A New Method for Micro-blog Platform Users Classification Based on Infinitesimal-time
In this paper, we propose the concept of infinitesimal-time slice and build infinitesimal-time model for micro-blog platform user classification problems. After researching on users in eachExpand
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Modeling Language Discrepancy for Cross-Lingual Sentiment Analysis
TLDR
Language discrepancy is inherent and be part of human languages. Expand
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A Part-of-Speech Enhanced Neural Conversation Model
TLDR
In this paper, we present two part-of-speech (POS) enhanced models that incorporate the POS information into the Seq2Seq neural conversation model. Expand
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Cross-Lingual Sentiment Relation Capturing for Cross-Lingual Sentiment Analysis
TLDR
We propose to capture the document-level sentiment connection across languages (called cross-lingual sentiment relation) for CLSA in a joint two-view convolutional neural networks (CNNs), namely Bi-View CNN (BiVCNN). Expand
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User Preference Modeling by Trust Propagation for Rating Prediction
TLDR
We propose a novel integrated matrix factorization framework to model user preference, trust relation and the relationship between them in a systematic way. Expand