6 papers
Scalable Exact Densest P-Partite Subgraph Search in Heterogeneous Information Networks
Jiadong Xie, Jiaming Yang, Kangfei Zhao +1
Heterogeneous information networks (HINs) model typed entities and typed relations, where dense cross-type structures can reveal cohesive semantic patterns such as prolific author-…
PLACE: Prompt Learning for Attributed Community Search in Large Graphs
Shuheng Fang, Kangfei Zhao, Rener Zhang +2
In this paper, we propose PLACE (Prompt Learning for Attributed Community Search), an innovative graph prompt learning framework for ACS. Enlightened by prompt-tuning in Natural La…
Sema: A High-performance System for LLM-based Semantic Query Processing
Kangkang Qi, Dongyang Xie, Wenbo Li +4
The integration of Large Language Models (LLMs) into data analytics has unlocked powerful capabilities for reasoning over bulk structured and unstructured data. However, existing s…
Beyond Linear LLM Invocation: An Efficient and Effective Semantic Filter Paradigm
Nan Hou, Kangfei Zhao, Jiadong Xie +1
Large language models (LLMs) are increasingly used for semantic query processing over large corpora. A set of semantic operators derived from relational algebra has been proposed t…
Can Large Language Models Be Query Optimizer for Relational Databases?
Jie Tan, Kangfei Zhao, Rui Li +6
Query optimization, which finds the optimized execution plan for a given query, is a complex planning and decision-making problem within the exponentially growing plan space in dat…
CardOOD: Robust Query-driven Cardinality Estimation under Out-of-Distribution
Rui Li, Kangfei Zhao, Jeffrey Xu Yu +1
Query-driven learned estimators are accurate, flexible, and lightweight alternatives to traditional estimators in query optimization. However, existing query-driven approaches stru…