---
title: "FACILE: Classifying Texts Integrating Pattern Matching and Information Extraction"
authors:
  - "Fabio Ciravegna"
  - "Alberto Lavelli"
  - "Luca Gilardoni"
  - "Johannes Matiasek"
  - "Nadia Mana"
  - "Silvia Mazza"
  - "Massimo Ferraro"
  - "William J. Black"
  - "Fabio Rinaldi"
  - "David Mowatt"
doi: ""
url: "https://ijcai.org/proceedings/1999/127"
pdf: "https://ijcai.org/proceedings/1999/0127.pdf"
venue: "Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence"
year: 1999
pages: "890-896"
track: "Natural Language Processing"
keywords:
---

# FACILE: Classifying Texts Integrating Pattern Matching and Information Extraction

Fabio Ciravegna, Alberto Lavelli, Luca Gilardoni, Johannes Matiasek, Nadia Mana, Silvia Mazza, Massimo Ferraro, William J. Black, Fabio Rinaldi, David Mowatt

*Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence*, pages 890-896.

## Abstract

Successfully managing information means being able to find relevant new information and to correctly integrate it with pre-existing knowledge. Much information is nowadays stored as multilingual textual data; therefore advanced classification systems are currently considered as strategic components for effective knowledge management. We describe an experie~ce integrating different innovative AI t~chnolog~es such as hierarchical pattern matchmg and mformation extraction to provide flexible multilingual classification adaptable to user needs. Pattern matching produces fairly accurate and fast categorisation over a large number of classes, while information extraction provides fine-grained classification for a reduced number of classes. The resulting system was adopted by the main Italian financial news agency providing a pay-to-view service.