Kai Zheng

Trigger3:Refining Query Correction via Adaptive Model Selector

2025 · Proceedings of the AAAI Conference on Artificial Intelligence

In search scenarios, user experience can be hindered by erroneous queries due to typos, voice errors, or knowledge gaps. Therefore, query correction is crucial for search engines. Current correction models, usually small models trained on …

Exploring JVM Garbage Collector Testing with Event-Coverage

2025 · ACM Transactions on Software Engineering and Methodology

Garbage Collection (GC) in the Java Virtual Machine (JVM) serves as an automatic memory management mechanism, efficiently reclaiming unused memory space in different production scenarios. To optimize JVM performance, developers typically fine-tune the garbage collector …

Adapting to User Interest Drift for POI Recommendation

2016 · IEEE Transactions on Knowledge and Data Engineering

Point-of-Interest recommendation is an essential means to help people discover attractive locations, especially when people travel out of town or to unfamiliar regions. While a growing line of research has focused on modeling user geographical …

Social Influence-Based Group Representation Learning for Group Recommendation

2019

As social animals, attending group activities is an indispensable part in people's daily social life, and it is an important task for recommender systems to suggest satisfying activities to a group of users. The major …

Multi-modal Knowledge Graphs for Recommender Systems

2020

Recommender systems have shown great potential to solve the information explosion problem and enhance user experience in various online applications. To tackle data sparsity and cold start problems in recommender systems, researchers propose knowledge graphs …