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GALACTIC core framework

GALACTIC framework io data plugin

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This is useful to reproduce common errors found in historical documents when historical data is missing.

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.

Requests to collect documents relating real-world events (themselves described using wikivents) stored in a global index (provided by database_infrastructure_text_mining).

This software is used to compute TF IDF weighting from texts that are based on the document_tracking_resources format. Vectors and weightings are computed thanks to a resource file that contains a representation of the language used in the same context as the text to weight (news features to weight texts published in the news).

Resources and Python API to manipulate datasets of news documents. It manipulates data in the .pickle format with the help of pandas and numpy. It can perform operations on the datasets.

Tools to manipulate the docufcn JSON file format that are used to represent segmentation in images.

ClimaBat experimental mockup - scaled-down street canyons in real-life climatic conditions