activity
20152026
most citedThe Future is Big Graphs! A Community View on Graph Processing Systems

157 citations · 168 across the 12 of their papers we have counts for

collaborators

12 papers

cs.DB2026

Even Faster Geosocial Reachability Queries

Rick van der Heijden, Nikolay Yakovets, Thekla Hamm

Geosocial reachability queries (\textsc{RangeReach}) determine whether a given vertex in a geosocial network can reach any spatial vertex within a query region. The state-of-the-ar…

cs.DB2026

Algorithm Support for Graph Databases, Done Right

Daan de Graaf, Robert Brijder, Soham Chakraborty +3

Graph database query languages cannot express algorithms like PageRank, forcing costly data wrangling, while existing solutions such as algorithm libraries, vertex-centric APIs, an…

cs.DB2025

On the feasibility of semantic query metrics

George Fletcher, Peter Wood, Nikolay Yakovets

We consider the problem of defining semantic metrics for relational database queries. Informally, a semantic query metric for a query language is a metric function $δ:L\times L…

cs.DB2024

Meta-Property Graphs: Extending Property Graphs with Metadata Awareness and Reification

Sepehr Sadoughi, Nikolay Yakovets, George Fletcher

The ISO standard Property Graph model has become increasingly popular for representing complex, interconnected data. However, it lacks native support for querying metadata and reif…

cs.DB2024★ 1 cited

Optimizing Navigational Graph Queries

Thomas Mulder, George Fletcher, Nikolay Yakovets

We study the optimization of navigational graph queries, i.e., queries which combine recursive and pattern-matching fragments. Current approaches to their evaluation are not effect…

cs.DB2024★ 1 cited

Discovering Graph Generating Dependencies for Property Graph Profiling

Larissa C. Shimomura, Nikolay Yakovets, George Fletcher

With the increasing use of graph-structured data, there is also increasing interest in investigating graph data dependencies and their applications, e.g., in graph data profiling.…

cs.DB2022

Reasoning on Property Graphs with Graph Generating Dependencies

Larissa C. Shimomura, Nikolay Yakovets, George Fletcher

Graph Generating Dependencies (GGDs) informally express constraints between two (possibly different) graph patterns which enforce relationships on both graph's data (via property v…

cs.DB2021★ 4 cited

A General Cardinality Estimation Framework for Subgraph Matching in Property Graphs

Wilco van Leeuwen, George Fletcher, Nikolay Yakovets

Many techniques have been developed for the cardinality estimation problem in data management systems. In this document, we introduce a framework for cardinality estimation of quer…

cs.DC2020★ 157 cited

The Future is Big Graphs! A Community View on Graph Processing Systems

Sherif Sakr, Angela Bonifati, Hannes Voigt +38

Graphs are by nature unifying abstractions that can leverage interconnectedness to represent, explore, predict, and explain real- and digital-world phenomena. Although real users a…

cs.DB2020

Answer Graph: Factorization Matters in Large Graphs

Zahid Abul-Basher, Nikolay Yakovets, Parke Godfrey +2

Our answer-graph method to evaluate SPARQL conjunctive queries (CQs) finds a factorized answer set first, an answer graph, and then finds the embedding tuples from this. This appro…

cs.DB2020★ 1 cited

GGDs: Graph Generating Dependencies

Larissa C. Shimomura, George Fletcher, Nikolay Yakovets

We propose Graph Generating Dependencies (GGDs), a new class of dependencies for property graphs. Extending the expressivity of state of the art constraint languages, GGDs can expr…

cs.DB2015★ 4 cited

Towards Query Optimization for SPARQL Property Paths

Nikolay Yakovets, Parke Godfrey, Jarek Gryz

The extension of SPARQL in version 1.1 with property paths offers a type of regular path query for RDF graph databases. Such queries are difficult to optimize and evaluate efficien…