Skip to content

NewsEye/event-detection

Repository files navigation

Event Detection

DAniEL (Data Analysis for Information Extraction in any Languages): event-detection-daniel

In the context of the NewsEye project where many languages are considered, the DAniEL system, created by Gaël Lejeune, was chosen. The system focuses on Epidemic Surveillance over press articles across multiple languages. Rather depending on language-specific grammars and analyzers, the system implements a string-based algorithm that detects repeated maximal substrings in salient zones to extract important information (disease name, location). The decision of choosing prominent text zones is based on the characteristics of a journalistic writing style where crucial information is usually put at the beginning and end of the article.

This is the Python 3 version of the Daniel System (originally from here: https://github.com/rundimeco/daniel)

Convolutional Neural Network model for event detection: event-detection-pytorch

Neural Methods for Event Extraction https://tel.archives-ouvertes.fr/tel-01943841/document

Releases

No releases published

Packages

No packages published

Contributors 4

  •  
  •  
  •  
  •  

Languages