About us

The goal of this workshop is to bring together researchers, practitioners and experts in entity resolution and graph alignment to introduce new methods and techniques, discuss open challenges, share benchmarks and explore future research directions across relational, graph-based and Linked Data environments.

Important Dates

Fri, Jun 12, 2026
Paper submission
Fri, Jun 26, 2026
Author notification
Fri, Jul 3, 2026
Camera-ready submission
Mon, Sep 28, 2026
Workshop

Call For Paper

Data fusion
Instance matching
Blocking and filtering for entity resolution
Named entity resolution
Collective entity resolution
Knowledge graph entity alignment
Knowledge graph completion and consolidation
LLM-assisted entity linking and graph merging
Ontology matching
Identity linking in Linked Data
Explainable AI for identity resolution
Cross-lingual entity alignment
Learning based approaches (supervised and unsupervised methods) to entity resolution and graph alignment
Representation learning for graph alignment
Deep learning based approaches for graph alignment
Crowdsourcing for entity resolution and graph alignment
Dynamic graph entity alignment
Streaming entity resolution
Entity resolution for big data
Parallel entity resolution
Privacy-preserving entity resolution and graph alignment
Fairness in entity resolution
Entity resolution for geospatial data
Empirical comparison of entity resolution methods
Benchmarks for entity resolution and graph alignment
Tools and platforms
Linked Data management

The workshop is calling for original LONG (up to 16 LNCS style pages) and SHORT (up to 10 LNCS style pages) papers that have not been published elsewhere.

Committee

Program Committee

ΤΒΑ

Organizing committee

Georgia Koloniari

University of Macedonia (Greece)

Alexandros Karakasidis

University of Macedonia / Athena RC (Greece)