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AEMIX: Verification of meteorological data by using text mining: The aim of this project is to verify the forecasts made by the Spanish National Meteorology Agency by using information extraction techniques based on this style guide, and comparing the results of the observations from the meteorology stations.

The AEMIX Project carried out by Gema Muñoz and Maria G. Buey, was presented in October 2014 by the GENIE Project Coordinator, Angel Luis Garrido at a conference cycle "AEMET Encounters".

The full presentation can be viewed in Youtube at this link: The Genie Project: AEMIX Project Conference at Aemet

Here are displayed some links on the web related to this conference:

Noticia Proyecto Genie Aemix en Aemet - Agencia Española de Meteorologianoticia-genie-aemix-aemet-aemet-ministeri.pngNoticia Proyecto Genie Aemix en Aemet - La Vanguardia Noticia Proyecto Genie Aemix en Aemet - EL Diario Vasco Noticia Proyecto Genie Aemix en Aemet - La InformacionNoticia Proyecto Genie Aemix en Aemet - El Economistanoticia-genie-aemix-aemet-EL Diario-Montanes
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Ex-GEO: Ontological Geotagging System: In this project Maria G. Buey and Sandra Escudero developed in 2013 a system that combines geographic location techniques with Natural Language Processing and statistical and semantic disambiguation tools to perform an appropriate geographical labeling of general natural language texts in a general way. The software can be fine-tuned for a given context in order to optimize the results.

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LAET: General Autotagging Library: The goal of this project was to develop a generalistic library in order to summarize and to tag texts by using machine learning, NLP tools and ontologies. The context information is supplied by using XML files and the architechture allows its integration with any kind of architectures. This project was developed during years 2012/2013 by Maria G. Buey, Alvaro Peiró and Sandra Escudero in the Labs of the University of Zaragoza.

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NASS: News Annotation Semantic System: Today in media companies there is a serious problem for cataloging news due to the large number of articles received by the documentation departments. That manual labor is subject to many errors and omissions because of the different points of view and expertise level of each staff member. There is also an additional difficulty due to the large size of the list of words in a thesaurus. In this project in colaboration with Heraldo de Aragon we have worked in a new method for solving the problem of text categorization over a corpus of newspaper articles where the annotation must be composed of thousands of thesaurus elements.

The NASS Project developed by Oscar Gómez and Angel Luis Garrido was presented in April 2012 at 7th Virtual Stores Trade Show in WALQA (Huesca).

The full presentation can be viewed in Youtube at this link: WALQA - Web Semantica - NASS News Annotation Semantic System