5 papers
Fully Inductive Cardinality Estimation
Tim Schwabe, Lukas Ketzer, Maribel Acosta
Query optimization of Basic Graph Patterns (BGP) SPARQL queries over Knowledge Graphs (KG) requires accurate cardinality estimation. Recently published learned estimators outperfor…
Gradient-Based Join Ordering
Tim Schwabe, Maribel Acosta
Join ordering is the NP-hard problem of selecting the most efficient order in which to evaluate joins (conjunctive, binary operators) in a database query. Because query execution p…
Effects of Distributional Biases on Gradient-Based Causal Discovery in the Bivariate Categorical Case
Tim Schwabe, Moritz Lange, Laurenz Wiskott +1
Gradient-based causal discovery shows great potential for deducing causal structure from data in an efficient and scalable way. Those approaches however can be susceptible to distr…
Q-NL Verifier: Leveraging Synthetic Data for Robust Knowledge Graph Question Answering
Tim Schwabe, Louisa Siebel, Patrik Valach +1
Question answering (QA) requires accurately aligning user questions with structured queries, a process often limited by the scarcity of high-quality query-natural language (Q-NL) p…
Neuro-Symbolic Query Optimization in Knowledge Graphs
Maribel Acosta, Chang Qin, Tim Schwabe
This chapter delves into the emerging field of neuro-symbolic query optimization for knowledge graphs (KGs), presenting a comprehensive exploration of how neural and symbolic techn…