77 citations · 110 across the 11 of their papers we have counts for
12 papers
Poseidon: A OneGraph Engine
Brad Bebee, Ümit V. Çatalyürek, Olaf Hartig +5
We present the Poseidon engine behind the Neptune Analytics graph database service. Customers interact with Poseidon using the declarative openCypher query language, which enables…
Evaluating the performance-deviation of itemKNN in RecBole and LensKit
Michael Schmidt, Jannik Nitschke, Tim Prinz
This study examines the performance of item-based k-Nearest Neighbors (ItemKNN) algorithms in the RecBole and LensKit recommender system libraries. Using four data sets (Anime, Mod…
Structured Evaluation of Synthetic Tabular Data
Scott Cheng-Hsin Yang, Baxter Eaves, Michael Schmidt +2
Tabular data is common yet typically incomplete, small in volume, and access-restricted due to privacy concerns. Synthetic data generation offers potential solutions. Many metrics…
Bridging graph data models: RDF, RDF-star, and property graphs as directed acyclic graphs
Ewout Gelling, George Fletcher, Michael Schmidt
Graph database users today face a choice between two technology stacks: the Resource Description Framework (RDF), on one side, is a data model with built-in semantics that was orig…
PG-Schema: Schemas for Property Graphs
Renzo Angles, Angela Bonifati, Stefania Dumbrava +18
Property graphs have reached a high level of maturity, witnessed by multiple robust graph database systems as well as the ongoing ISO standardization effort aiming at creating a ne…
Graph? Yes! Which one? Help!
Ora Lassila, Michael Schmidt, Brad Bebee +6
Amazon Neptune is a graph database service that supports two graph (meta)models: W3C's Resource Description Framework (RDF) and Labeled Property Graphs (LPG). Customers opt in for…