57 citations · 191 across the 6 of their papers we have counts for
6 papers
Deep Learning for Sentiment Analysis : A Survey
Lei Zhang, Shuai Wang, Bing Liu
Deep learning has emerged as a powerful machine learning technique that learns multiple layers of representations or features of the data and produces state-of-the-art prediction r…
Contextual and Position-Aware Factorization Machines for Sentiment Classification
Shuai Wang, Mianwei Zhou, Geli Fei +2
While existing machine learning models have achieved great success for sentiment classification, they typically do not explicitly capture sentiment-oriented word interaction, which…
Unseen Class Discovery in Open-world Classification
Lei Shu, Hu Xu, Bing Liu
This paper concerns open-world classification, where the classifier not only needs to classify test examples into seen classes that have appeared in training but also reject exampl…
Lifelong Learning for Sentiment Classification
Zhiyuan Chen, Nianzu Ma, Bing Liu
This paper proposes a novel lifelong learning (LL) approach to sentiment classification. LL mimics the human continuous learning process, i.e., retaining the knowledge learned from…
Context-aware Path Ranking for Knowledge Base Completion
Sahisnu Mazumder, Bing Liu
Knowledge base (KB) completion aims to infer missing facts from existing ones in a KB. Among various approaches, path ranking (PR) algorithms have received increasing attention in…
DOC: Deep Open Classification of Text Documents
Lei Shu, Hu Xu, Bing Liu
Traditional supervised learning makes the closed-world assumption that the classes appeared in the test data must have appeared in training. This also applies to text learning or t…