# JRC EuroVoc Indexer JEX - A freely available multi-label categorisation tool

arXiv: https://arxiv.org/abs/1309.5223 · HTML: https://mlsanity.com/paper/1309.5223/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Sep 2013.

## Built on by (most cited first, 3 of 3)

- [PyEuroVoc: A Tool for Multilingual Legal Document Classification with EuroVoc Descriptors](https://mlsanity.com/paper/2108.01139/) (2021)
- [MADE: A Living Benchmark for Multi-Label Text Classification with Uncertainty Quantification of Medical Device Adverse Events](https://mlsanity.com/paper/2604.15203/) (2026)
- [RELATE: A Modern Processing Platform for Romanian Language](https://mlsanity.com/paper/2410.21778/) (2024)

## Abstract (arXiv)

EuroVoc (2012) is a highly multilingual thesaurus consisting of over 6,700 hierarchically organised subject domains used by European Institutions and many authorities in Member States of the European Union (EU) for the classification and retrieval of official documents. JEX is JRC-developed multi-label classification software that learns from manually labelled data to automatically assign EuroVoc descriptors to new documents in a profile-based category-ranking task. The JEX release consists of trained classifiers for 22 official EU languages, of parallel training data in the same languages, of an interface that allows viewing and amending the assignment results, and of a module that allows users to re-train the tool on their own document collections. JEX allows advanced users to change the document representation so as to possibly improve the categorisation result through linguistic pre-processing. JEX can be used as a tool for interactive EuroVoc descriptor assignment to increase speed and consistency of the human categorisation process, or it can be used fully automatically. The output of JEX is a language-independent EuroVoc feature vector lending itself also as input to various other Language Technology tasks, including cross-lingual clustering and classification, cross-lingual plagiarism detection, sentence selection and ranking, and more.