CLSep 20, 2013

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

arXiv:1309.5223v150 citations
Originality Synthesis-oriented
AI Analysis

This tool addresses the need for efficient and consistent classification of multilingual official documents for European institutions and authorities, though it is incremental as it builds on existing EuroVoc thesaurus and classification methods.

The paper tackles the problem of automatically assigning EuroVoc descriptors to documents in 22 EU languages, resulting in a freely available multi-label classification tool (JEX) that can be used interactively or fully automatically to improve speed and consistency in categorizing official documents.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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