Expert Finding for Community-Based Question Answering via Ranking Metric Network Learning

By Zhou Zhao, Qifan Yang, Deng Cai, Xiaofei He, Yueting Zhuang. 2016

89 citations recorded by the source corpus.

How researchers see this paper

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

1. Deng Cai
2. Zhou Zhao
3. Xiaofei He
4. Hanqing Lu
5. Yueting Zhuang
6. Vincent Wenchen Zheng
7. Feiping Nie
8. Qifan Yang

Citations in the corpus

• Community-Based Question Answering via Asymmetric Multi-Faceted Ranking Network Learning (2017, background): “Nowadays the community-based question answering (CQA) sites become the popular Internet-based web service, which have accumulated millions of questions and their posted answers over time (Zhao et al. 2016b).”
• Video Question Answering via Hierarchical Spatio-Temporal Attention Networks (2017, methodology): “Following the existing question answering approaches [Antol et al., 2015; Shih et al., 2016; Yang et al., 2016; Zhao et al., 2015; 2016], we generate four types of questions, which are related to the object, number, color and location queries for the video.”