8 citations · 8 across the 1 of their papers we have counts for
8 papers
Recommender Systems for the Internet of Things: A Survey
May Altulyan, Lina Yao, Xianzhi Wang +3
Recommendation represents a vital stage in developing and promoting the benefits of the Internet of Things (IoT). Traditional recommender systems fail to exploit ever-growing, dyna…
Knowledge-guided Deep Reinforcement Learning for Interactive Recommendation
Xiaocong Chen, Chaoran Huang, Lina Yao +3
Interactive recommendation aims to learn from dynamic interactions between items and users to achieve responsiveness and accuracy. Reinforcement learning is inherently advantageous…
Software Expert Discovery via Knowledge Domain Embeddings in a Collaborative Network
Chaoran Huang, Lina Yao, Xianzhi Wang +2
Community Question Answering (CQA) websites can be claimed as the most major venues for knowledge sharing, and the most effective way of exchanging knowledge at present. Considerin…
Brain2Object: Printing Your Mind from Brain Signals with Spatial Correlation Embedding
Xiang Zhang, Lina Yao, Chaoran Huang +3
Electroencephalography (EEG) signals are known to manifest differential patterns when individuals visually concentrate on different objects. In this work, we present an end-to-end…
Expert Recommendation via Tensor Factorization with Regularizing Hierarchical Topical Relationships
Chaoran Huang, Lina Yao, Xianzhi Wang +3
Knowledge acquisition and exchange are generally crucial yet costly for both businesses and individuals, especially when the knowledge concerns various areas. Question Answering Co…
A Survey on Expert Recommendation in Community Question Answering
Xianzhi Wang, Chaoran Huang, Lina Yao +2
Community question answering (CQA) represents the type of Web applications where people can exchange knowledge via asking and answering questions. One significant challenge of most…