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GALACTIC framework io data plugin

GALACTIC core framework

This software enables to damage texts written in any natural language by applying OCR degradation (phantom characters, character degradation, etc.) and by over-segmenting texts (this means splitting regularly the texts in equal parts).

This is useful to reproduce common errors found in historical documents when historical data is missing.

Learning Management Systems like Moodle generate detailed logs from student interactions, offering significant potential for learning analytics and educational process mining. However, raw logs capture interaction-based actions rather than actual learning processes, limiting their pedagogical relevance. To address this, we developed Moodle2EventLog, a tool that automates the cleaning, preprocessing, and semantic enrichment of Moodle logs. The tool operates in two modules: the first cleans and structures logs by generating event logs with key elements (case IDs, activities, timestamps), and the second enriches them by grouping low-level events into context-aware sub-processes and maps them to "Semantic Activities" based on Bloom’s Taxonomy.

Projet basculé sur gitlab-dsi (https://gitlab-dsi.univ-lr.fr/dsi-soft/audiovisuel/linx)

This software is used to compute dense vectorisations (sentence embeddings) of sequences of sentences of natural text. It is able to handle multilingual documents until the model used is a multilingual one. This relies on the S-BERT architecture, software and models (https://www.sbert.net/). It computes dense vector representations for tokens, lemmas, entities, etc. of your datasets.