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Author (down) Stephen Potter; Yannis Kalfoglou; Harith Alani; Michelle Bachler; Simon Buckingham Shum; Rodrigo Carvalho; Ajay Chakravarthy; Stuart Chalmers; Sam Chapman; Beibei Hu; Alun Preece; Nigel Shadbolt; Austin Tate; Mischa Tuffield
Title The application of advanced knowledge technologies for emergency response Type Conference Article
Year 2007 Publication Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers Abbreviated Journal ISCRAM 2007
Volume Issue Pages 361-368
Keywords Artificial intelligence; Decision support systems; Decision supports; Emergency response; Intelligent messaging; Semantic technologies; Sensemaking; Emergency services
Abstract Making sense of the current state of an emergency and of the response to it is vital if appropriate decisions are to be made. This task involves the acquisition, interpretation and management of information. In this paper we present an integrated system that applies recent ideas and technologies from the fields of Artificial Intelligence and semantic web research to support sense-and decision-making at the tactical response level, and demonstrate it with reference to a hypothetical large-scale emergency scenario. We offer no end-user evaluation of this system; rather, we intend that it should serve as a visionary demonstration of the potential of these technologies for emergency response.
Address University of Edinburgh, United Kingdom; University of Southampton, United Kingdom; Open University, United Kingdom; University of Sheffield, United Kingdom; University of Aberdeen, United Kingdom
Corporate Author Thesis
Publisher Information Systems for Crisis Response and Management, ISCRAM Place of Publication Delft Editor B. Van de Walle, P. Burghardt, K. Nieuwenhuis
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 9789054874171; 9789090218717 Medium
Track ASCM Expedition Conference 4th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 852
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Author (down) Grégoire Burel; Lara S. G. Piccolo; Kenny Meesters; Harith Alani
Title DoRES -- A Three-tier Ontology for Modelling Crises in the Digital Age Type Conference Article
Year 2017 Publication Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management Abbreviated Journal Iscram 2017
Volume Issue Pages 834-845
Keywords Crisis Ontology; Situation Awareness; Emergency Model; Events; Reports
Abstract During emergency crises it is imperative to collect, organise, analyse and share critical information between individuals and humanitarian organisations. Although dierent models and platforms have been created for helping these particular issues, existing work tend to focus on only one or two of the previous matters. We propose the DoRES ontology for representing information sources, consolidating it into reports and then, representing event situation based on reports. Our approach is guided by the analysis of 1) the structure of a widely used situation awareness platform; 2) stakeholder interviews, and; 3) the structure of existing crisis datasets. Based on this, we extract 102 dierent competency questions that are then used for specifying and implementing the new three-tiers crisis model. We show that the model can successfully be used for mapping the 102 dierent competency questions to the classes, properties and relations of the implemented ontology.
Address Knowledge Media Institute (KMi), The Open University, Milton Keynes, United Kingdom; Centre for Integrated Emergency Management (CIEM), University of Agder Kristiansand, Norway
Corporate Author Thesis
Publisher Iscram Place of Publication Albi, France Editor Tina Comes, F.B., Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN Medium
Track New Technologies for Crisis Management Expedition Conference 14th International Conference on Information Systems for Crisis Response And Management
Notes Approved no
Call Number Serial 2069
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Author (down) Grégoire Burel; Harith Alani
Title Crisis Event Extraction Service (CREES) – Automatic Detection and Classification of Crisis-related Content on Social Media Type Conference Article
Year 2018 Publication ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2018
Volume Issue Pages 597-608
Keywords Event Detection, Word Embeddings, Deep Learning, Convolutional Neural Networks, API
Abstract Social media posts tend to provide valuable reports during crises. However, this information can be hidden in large amounts of unrelated documents. Providing tools that automatically identify relevant posts, event types (e.g., hurricane, floods, etc.) and information categories (e.g., reports on affected individuals, donations and volunteering, etc.) in social media posts is vital for their efficient handling and consumption. We introduce the Crisis Event Extraction Service (CREES), an open-source web API that automatically classifies posts during crisis situations. The API provides annotations for crisis-related documents, event types and information categories through an easily deployable and accessible web API that can be integrated into multiple platform and tools. The annotation service is backed by Convolutional Neural Networks (CNNs) and validated against traditional machine learning models. Results show that the CNN-based API results can be relied upon when dealing with specific crises with the benefits associated with the usage word embeddings.
Address
Corporate Author Thesis
Publisher Rochester Institute of Technology Place of Publication Rochester, NY (USA) Editor Kees Boersma; Brian Tomaszeski
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 978-0-692-12760-5 Medium
Track Social Media Studies Expedition Conference ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 2134
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