JsonGrinder.jl
is a library that facilitates processing of JSON documents into
Mill.jl
structures for machine learning. It provides
functionality for JSON schema inference, extraction of JSON documents to a suitable representation
for machine learning, and constructing a model operating on this data.
Watch our introductory talk from JuliaCon 2021.
Run the following in REPL:
] add JsonGrinder
Kindly cite our work with the following entries if you find it interesting, please:
-
JsonGrinder.jl: automated differentiable neural architecture for embedding arbitrary JSON data
@article{Mandlik2021, author = {Šimon Mandlík and Matěj Račinský and Viliam Lisý and Tomáš Pevný}, title = {JsonGrinder.jl: automated differentiable neural architecture for embedding arbitrary JSON data}, journal = {Journal of Machine Learning Research}, year = {2022}, volume = {23}, number = {298}, pages = {1--5}, url = {http://jmlr.org/papers/v23/21-0174.html} }
-
Malicious Internet Entity Detection Using Local Graph Inference (practical
Mill.jl
andJsonGrinder.jl
application)@article{Mandlik2024, author = {Mandlík, Šimon and Pevný, Tomáš and Šmídl, Václav and Bajer, Lukáš}, journal = {IEEE Transactions on Information Forensics and Security}, title = {Malicious Internet Entity Detection Using Local Graph Inference}, year = {2024}, volume = {19}, pages = {3554-3566}, doi = {10.1109/TIFS.2024.3360867} }
-
this implementation (fill in the used
version
):@software{JsonGrinder, author = {Tomas Pevny and Matej Racinsky and Simon Mandlik}, title = {JsonGrinder.jl: a flexible library for automated feature engineering and conversion of JSONs to Mill.jl structures}, url = {https://github.com/CTUAvastLab/JsonGrinder.jl}, version = {...}, }
If you want to contribute to JsonGrinder.jl, be sure to review the contribution guidelines.
We use GitHub issues for tracking requests and bugs.