Publication
TrendMiner: Large-scale Cross-lingual Trend Mining Summarization of Real-time Media Streams
Paloma Martínez; Isabel Segura; Thierry Declerck; José L. Martínez
In: Proceedings of the XXX Conference of the Spanish Society for Natural Language Processing. Conference of the Spanish Society for Natural Language Processing (SEPLN-14), September 16-19, Girona, Spain, SEPL, 9/2014.
Abstract
The recent massive growth in online media and the rise of user-authored content (e.g weblogs, Twitter, Facebook) has led to challenges of how to access and interpret the strongly multilingual data, in a timely, efficient, and affordable manner. The goal of this project is to deliver innovative, portable open-source real-time methods for cross-lingual mining and summarization of large-scale stream media. Results are validated in three high-profile case studies: financial decision support (with analysts, traders, regulators, and economists), political analysis and monitoring (with politicians, economists, and political journalists) and monitoring patient postings in the health domain to detect adverse drug reactions.