Mining Aspect-Specific Opinion using a Holistic Lifelong Topic Model

By Shuai Wang, Zhiyuan Chen, Bing Liu. 2016

135 citations recorded by the source corpus.

Subfields: Artificial Intelligence

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Bing Liu
2. Hu Xu
3. Lei Shu
4. B. Liu
5. Sahisnu Mazumder
6. Zixuan Ke
7. Shuai Wang
8. Geli Fei

Citations in the corpus

• Lifelong Generative Modeling (2017, background): “In parallel, lifelong learning was extended to independent multi-task learning [107, 31], reinforcement learning [125, 122, 102], topic modeling [19, 130] and semi-supervised language learning [83, 81].”
• Lifelong Learning CRF for Supervised Aspect Extraction (2017, background): “…2010; Wang et al., 2010; Moghaddam and Ester, 2011; Mukherjee and Liu, 2012; Lin and He, 2009; Zhao et al., 2010; Jo and Oh, 2011; Fang and Huang, 2012; Wang et al., 2016), word alignment (Liu et al., 2013), label propagation (Zhou et al., 2013; Shu et al., 2016), and others (Zhao et al., 2015).”
• Lifelong Learning Memory Networks for Aspect Sentiment Classification (2018, methodology): “terms of sentiment analysis, LML has been used to tackle aspect extraction [28], [29], opinion mining [30] and documentlevel sentiment classification [31].”