Project Highlites: A simple yet useful open source solution for classification predictions, based solely on your data

Author(s)
Keywords

subject classificatio...

artificial intelligen...

research information ...

ECOOM

Wander

Issue Date
May 20, 2026
Publisher
euroCRIS
Type
Conference Poster
Abstract
Subject classification of publications, projects and other entities is ubiquitous in CRIS systems. This project arose from practical considerations: how could we easily use AI to facilitate the cris administrator's work? This led to an application that can be deployed in various settings: given a brief textual description (e.g., a title and/or abstract of a publication), the application can generate one or more proposals for subject cataloguing. This can be implemented directly in various settings and for different types of classifications. Given sufficient training material, the application can be used with any classification system. We initially considered limited UDC coding for internal use, but also the retroactive assignment of so-called VODS codes, a scheme developed within the framework of the Flemish ECOOM project.
Description
Presented at the CRIS2026 poster session.-- Includes extended abstract
URI
https://dspacecris.eurocris.org/handle/11366/9467
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CRIS2026_paper-30_Descamps_Project-Highlites_extended-abstract.pdf

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Extended abstract
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50.51 KB

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Adobe PDF

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CRIS2026_Descamps_poster_Highlites-Antwerpen.pdf

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Poster
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952.91 KB

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Adobe PDF

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