2017
EACL
EACL 2017
Marine Variable Linker: Exploring Relations between Changing Variables in Marine Science Literature
Abstract
AbstractWe report on a demonstration system for text mining of literature in marine science and related disciplines. It automatically extracts variables (“CO2”) involved in events of change/increase/decrease (“increasing CO2”), as well as co-occurrence and causal relations among these events (“increasing CO2 causes a decrease in pH in seawater”), resulting in a big knowledge graph. A web-based graphical user interface targeted at marine scientists facilitates searching, browsing and visualising events and their relations in an interactive way.
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Interdisciplinary Bridge
— Artificial Intelligence and Data Science & Analytics and Knowledge & Reasoning and Natural Language Processing
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Keyword Pioneer
— variable extraction
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Hot Topic Early Bird
— text mining
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio