115 citations · 369 across the 83 of their papers we have counts for
6 papers · 1 filter
Uncover Sexual Harassment Patterns from Personal Stories by Joint Key Element Extraction and Categorization
Yingchi Liu, Quanzhi Li, Marika Cifor +3
The number of personal stories about sexual harassment shared online has increased exponentially in recent years. This is in part inspired by the \#MeToo and \#TimesUp movements. S…
Human-Like Decision Making: Document-level Aspect Sentiment Classification via Hierarchical Reinforcement Learning
Jingjing Wang, Changlong Sun, Shoushan Li +5
Recently, neural networks have shown promising results on Document-level Aspect Sentiment Classification (DASC). However, these approaches often offer little transparency w.r.t. th…
Cross-domain Aspect Category Transfer and Detection via Traceable Heterogeneous Graph Representation Learning
Zhuoren Jiang, Jian Wang, Lujun Zhao +3
Aspect category detection is an essential task for sentiment analysis and opinion mining. However, the cost of categorical data labeling, e.g., label the review aspect information…
Detect Camouflaged Spam Content via StoneSkipping: Graph and Text Joint Embedding for Chinese Character Variation Representation
Zhuoren Jiang, Zhe Gao, Guoxiu He +5
The task of Chinese text spam detection is very challenging due to both glyph and phonetic variations of Chinese characters. This paper proposes a novel framework to jointly model…
AMAD: Adversarial Multiscale Anomaly Detection on High-Dimensional and Time-Evolving Categorical Data
Zheng Gao, Lin Guo, Chi Ma +6
Anomaly detection is facing with emerging challenges in many important industry domains, such as cyber security and online recommendation and advertising. The recent trend in these…
Neural Related Work Summarization with a Joint Context-driven Attention Mechanism
Yongzhen Wang, Xiaozhong Liu, Zheng Gao
Conventional solutions to automatic related work summarization rely heavily on human-engineered features. In this paper, we develop a neural data-driven summarizer by leveraging th…