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Real-Time Discovery and Geospatial Visualization of Mobility and Industry Events from Large-Scale, Heterogeneous Data Streams
Citation key HennigTAKWPZSXO16
Author Leonhard Hennig; Philippe Thomas; Renlong Ai; Johannes Kirschnick; He Wang; Jakob Pannier; Nora Zimmermann; Sven Schmeier; Feiyu Xu; Jan Ostwald; Hans Uszkoreit
Year 2016
Journal Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics. Annual Meeting of the Association for Computational Linguistics (ACL-16)
Volume 54
Abstract Monitoring mobility- and industryrelevant events is important in areas such as personal travel planning and supply chain management, but extracting events pertaining to specific companies, transit routes and locations from heterogeneous, high-volume text streams remains a significant challenge. We present Spree, a scalable system for real-time, automatic event extraction from social media, news and domain-specific RSS feeds. Our system is tailored to a range of mobilityand industry-related events, and processes German texts within a distributed linguistic analysis pipeline implemented in Apache Flink. The pipeline detects and disambiguates highly ambiguous domain-relevant entities, such as street names, and extracts various events with their geo-locations. Event streams are visualized on a dynamic, interactive map for monitoring and analysis.
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