Xiangjie Kong

Scientific Paper Recommendation: A Survey

2020 · IEEE Access

Globally, the recommendation services have become important due to the fact that they support e-commerce applications and different research communities. Recommender systems have a large number of applications in many fields, including economic, education, and …

Point-Correlate Adversarial Transformer for Unsupervised Multivariate Time Series Anomaly Detection

2024

Multivariate time series anomaly detection plays a crucial role in industrial production. However, the inherent complexity and randomness of time series pose significant challenges. Furthermore, existing detection methods struggle to provide reliable explanations for outliers. …

VOPRec: Vector Representation Learning of Papers with Text Information and Structural Identity for Recommendation

2018 · IEEE Transactions on Emerging Topics in Computing

Finding relevant papers is a non-trivial problem for scholars due to the tremendous amount of academic information in the era of scholarly big data. Scientific paper recommendation systems have been developed to solve such problem …

A Survey of Collaborative Filtering-Based Recommender Systems: From Traditional Methods to Hybrid Methods Based on Social Networks

2018 · IEEE Access

In the era of big data, recommender system (RS) has become an effective information filtering tool that alleviates information overload for Web users. Collaborative filtering (CF), as one of the most successful recommendation techniques, has …