privJedAI

privJedAI#

Overview#

privJedAI is a python framework, aiming to offer experts and novice users, robust and fast solutions for Privacy Preserving Record Linkage. It is builded using state-of-the-art python frameworks. privJedAI constitutes the sole open-source Link Discovery tool that is capable of exploiting the latest breakthroughs in Deep Learning and NLP techniques, which are publicly available through the Python data science ecosystem. This applies to both blocking and matching, thus ensuring high time efficiency, high scalability as well as high effectiveness, without requiring any labelled instances from the user.

Key-Features#

  • Input data-type independent. Both structured and semi-structured data can be processed.

  • Various implemented algorithms.

  • Easy-to-use.

  • Utilizes some of the famous and cutting-edge machine learning packages.

  • Offers supervised and un-supervised ML techniques.

Install#

privJedAI has been tested on Linux OS.

PyPI

Install the latest version of pyjedai:

pip install privjedai

More on PyPI.

Git

Set up locally:

git clone https://github.com/AI-team-UoA/privJedAI.git

go to the root directory with cd privJedAI and type:

pip install .

Tutorials#

Find all the code of the tutotials in the privjedai/tutorials folder.

Simple use case
Detailed notebook

Dependencies#

         



See the full list of dependencies and all versions used, in this file.

Statistics & Info

PyPI - Downloads PyPI version

Bugs, Discussions & News#

GitHub Discussions is the discussion forum for general questions and discussions and our recommended starting point. Please report any bugs that you find here. –>

Team & Authors#

Lefteris Stetsikas

Research Associate at University of Athens

Dimitrios Karapiperis

Senior Researcher at International Hellenic University

George Papadakis

Postdoctoral Researcher at University of AthensEntity Resolution expert

Manolis Koubarakis

Professor at University of Athens

Research and development is made under the supervision of Pr. Manolis Koubarakis. This is a research project by the AI-Team of the Department of Informatics and Telecommunications at the University of Athens.

License#

Released under the Apache-2.0 license (see LICENSE.txt).

Copyright © 2026 AI-Team, University of Athens

Acknowledgements#

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This work was supported by the Horizon Europe project RECITALS (Grant No.101168490.).


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