67 citations · 243 across the 18 of their papers we have counts for
5 papers · 1 filter
GRACE: Gradient Harmonized and Cascaded Labeling for Aspect-based Sentiment Analysis
Huaishao Luo, Lei Ji, Tianrui Li +2
In this paper, we focus on the imbalance issue, which is rarely studied in aspect term extraction and aspect sentiment classification when regarding them as sequence labeling tasks…
Distributional Discrepancy: A Metric for Unconditional Text Generation
Ping Cai, Xingyuan Chen, Peng Jin +2
The purpose of unconditional text generation is to train a model with real sentences, then generate novel sentences of the same quality and diversity as the training data. However,…
Learning with Noisy Labels for Sentence-level Sentiment Classification
Hao Wang, Bing Liu, Chaozhuo Li +2
Deep neural networks (DNNs) can fit (or even over-fit) the training data very well. If a DNN model is trained using data with noisy labels and tested on data with clean labels, the…
DOER: Dual Cross-Shared RNN for Aspect Term-Polarity Co-Extraction
Huaishao Luo, Tianrui Li, Bing Liu +1
This paper focuses on two related subtasks of aspect-based sentiment analysis, namely aspect term extraction and aspect sentiment classification, which we call aspect term-polarity…
Improving Aspect Term Extraction with Bidirectional Dependency Tree Representation
Huaishao Luo, Tianrui Li, Bing Liu +2
Aspect term extraction is one of the important subtasks in aspect-based sentiment analysis. Previous studies have shown that using dependency tree structure representation is promi…