Towards Explainable Text Classification by Jointly Learning Lexicon and Modifier Terms

By Jérémie Clos, Nirmalie Chandrika Wiratunga, Stewart Massie. 2017

Subfields: Natural Language Processing

How researchers see this paper

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

In Natural Language Processing

1. Heike Adel
2. Giuseppe Di Fatta
3. Mario Cannataro
4. Huizhi Liang
5. Ngoc Thang Vu
6. Hendrik Schuff
7. Chiara Zucco
8. Ana Marasovic

Citations in the corpus

• F1 Is Not Enough! Models and Evaluation towards User-Centered Explainable Question Answering (2020, background): “, 2018), sentiment classification (Clos et al., 2017), machine translation (Stahlberg et al.”
• Explainable Artificial Intelligence: a Systematic Review (2020, unknown): “RELEXNET uses lexicons as inputs of a naive gated recurrent neural network which returns the probability that the input belongs or not to a certain class.”
• Explainable Sentiment Analysis with Applications in Medicine (2018, background): “[63] proposes a hybrid classification model that performs lexicon based classification by using a lexicon generated with a learning procedure.”