Extraction of Geospatial References from Free Text Based on Natural Language Processing and Accessibility Theory

La extracción automática de información geoespacial en tiempo real, a partir de discurso libre, tendrá un enorme impacto en tecnologías disruptivas, tales como los asistentes inteligentes y los motores de búsqueda. Generar modelos capaces de decodificar el discurso para luego transformarlo en datos estructurados aborda la solución de problemas como: la identificación automática de frases que se refieran a alguna entidad geoespacial; el manejo de sinónimos referidos a una misma locación (ambiguedad); la caracterización taxonómica de expresiones locativas; así como la automatización de procesos complejos de interpretación del lenguaje para la determinación de coordenadas geográficas en mapas y bases de datos. El proyecto presentado tiene por objetivo la automatización de procesos de georeferencia de documentos digitales para extraer conocimiento. La propuesta metodológica incluye compilación de un corpus, caracterización lingüística y desarrollo de algoritmos.The automatic extraction of geospatial information in real time, from free speech, will an important impact on disruptive technologies, such as AI assistants and search engines. Models capable of decoding discourse and then transforming it into structured data addresses the solution of challenging problems such as: the automatic identification of phrases refering geospatial entities; the handling of synonyms referring to the same location (ambiguity); the taxonomic characterization of locative expressions; as well as the automation of complex processes of natural language interpretation to determine of geographical coordinates, maps and databases. The presented project aims to automate georeferencing processes of digital documents to extract georeferenced knowledge. The methodological proposal includes compilation of a corpus, linguistic characterization and algorithms.Proyecto FORDECyT 296737 (Consorcio en Inteligencia Artificial) y a la Red Temática en Tecnologías del Lenguaje por el financiamiento parcial de esta investigación

Monitoring holopelagic Sargassum spp. along the Mexican Caribbean coast: understanding and addressing user requirements for satellite remote sensing

Massive influxes of holopelagic Sargassum spp. (Sargassum natans and S. fluitans) have been causing major economic, environmental and ecological problems along the Caribbean coast of Mexico. Predicting the arrival of the sargassum as an aid to addressing these problems is a priority for the government, coastal communities and the society; both mitigating the impacts and providing opportunities for its use. Lack of data concerning precise locations and times of sargassum beachings means that public and private funds are being spent inefficiently and most actions are reactive. The dynamic nature of sargassum beachings/influxes render conventional ground-based monitoring insufficient. Earth observation and cloud-based processing services offer tools to track, quantify and understand sargassum beaching remotely in a frequent, systematic and reliable manner with the temporal and spatial resolutions required for its management. In order to find the right solutions to address this problem, in this paper the needs and requirements of stakeholders are taken into consideration for the development of an Earth observation-based service to monitor sargassum along the Mexican Caribbean coast. Routine monitoring of sargassum over a large area will be cost effective and help mitigate the negative effects of sargassum influxes. The combination of imagery from Planet, specifically their SuperDove systems that provide daily data at 3 m spatial resolutions, with the freely available EU Copernicus data would be useful for many different stakeholders and potential users. A prototype of the service is presented, based on the main user requirements. The system would enable public and private organizations to allocate resources appropriately in affected areas quickly and efficiently, thereby minimizing economic, social and environmental impacts and enhancing the resilience of local communities. It would also assist the sargassum industry in the collection of fresh algae for onward processing. The system could easily be implemented for similar types of environmental monitoring in the Greater Caribbean and beyond

Sentiment Analysis for Twitter: TASS 2015 *

Resumen: En este artículo se presentan los resultados obtenidos en la tarea 1: clasificación global de cinco niveles de polaridad para un conjunto de tweets en español, del reto TASS 2015. En nuestra metodología, la representación de los tweets estuvo basada en características lingüisticas y de polaridad como lematizado de palabras, filtros de palabras, reglas de negación, entre otros. Además, se utilizaron diferentes transformaciones como LDA, LSI y la matriz TF-IDF, todas estas representaciones se combinaron con el clasificador SVM. Los resultados muestran que LSI y la matriz TF-IDF mejoran el rendimiento del clasificador SVM utilizado. Palabras clave: Análisis de sentimiento, Minería de opinión, Twitter Abstract: In this paper we present experiments for global polarity classification task of Spanish tweets for TASS 2015 challenge. In our methodology, tweets representation is focused on linguistic and polarity features such as lemmatized words, filter of content words, rules of negation, among others. In addition, different transformations are used (LDA, LSI, and TF-IDF) and combined with a SVM classifier. The results show that LSI and TF-IDF representations improve the performance of the SVM classifier applied