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- research-articleFebruary 2022
Understanding and Improvement of Adversarial Training for Network Embedding from an Optimization Perspective
WSDM '22: Proceedings of the Fifteenth ACM International Conference on Web Search and Data MiningFebruary 2022, Pages 230–240https://doi.org/10.1145/3488560.3498474Network Embedding aims to learn a function mapping the nodes to Euclidean space contribute to multiple learning analysis tasks on networks. However, both the noisy information behind the real-world networks and the overfitting problem negatively impact ...
- research-articleFebruary 2022
Choosing the Best of Both Worlds: Diverse and Novel Recommendations through Multi-Objective Reinforcement Learning
WSDM '22: Proceedings of the Fifteenth ACM International Conference on Web Search and Data MiningFebruary 2022, Pages 957–965https://doi.org/10.1145/3488560.3498471Since the inception of Recommender Systems (RS), the accuracy of the recommendations in terms of relevance has been the golden criterion for evaluating the quality of RS algorithms. However, by focusing on item relevance, one pays a significant price in ...
- research-articleFebruary 2022
On Generalizing Static Node Embedding to Dynamic Settings
WSDM '22: Proceedings of the Fifteenth ACM International Conference on Web Search and Data MiningFebruary 2022, Pages 410–420https://doi.org/10.1145/3488560.3498428Temporal graph embedding has been widely studied thanks to its superiority in tasks such as prediction and recommendation. Despite the advances in algorithms and novel frameworks such as deep learning, there has been relatively little work on ...
- research-articleFebruary 2022
Structure Meets Sequences: Predicting Network of Co-evolving Sequences
WSDM '22: Proceedings of the Fifteenth ACM International Conference on Web Search and Data MiningFebruary 2022, Pages 1090–1098https://doi.org/10.1145/3488560.3498411Co-evolving sequences are ubiquitous in a variety of applications, where different sequences are often inherently inter-connected with each other. We refer to such sequences, together with their inherent connections modeled as a structured network, as ...
- research-articleFebruary 2022
AdaptKT: A Domain Adaptable Method for Knowledge Tracing
WSDM '22: Proceedings of the Fifteenth ACM International Conference on Web Search and Data MiningFebruary 2022, Pages 123–131https://doi.org/10.1145/3488560.3498379Knowledge tracing is a crucial and fundamental task in online education systems, which can predict students' knowledge state for personalized learning. Unfortunately, existing methods are domain-specific, whereas there are many domains (e.g., subjects, ...