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Maarten Van Someren, Niels Netten, Vanessa Evers, Henriette Cramer, Robert De Hoog, & Guido Bruinsma. (2005). A trainable information distribution system to support crisis management. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 203–206). Brussels: Royal Flemish Academy of Belgium.
Abstract: Crisis response and management involve multiple collaborative actors who execute tasks in a dynamic setting. For the effectiveness of collaboration and crisis fighting it is essential that all actors have access to relevant information necessary for their tasks. Managing the information flow, i.e. presenting the right information to the right person at the right time, is of great importance. However, the complexity of a crisis event makes it very difficult to keep an overview of all ongoing activities and information flow within the entire crisis environment. In this paper we address the problem of selecting and distributing information to users as a function of their characteristics, tasks and the state of their workflows in a collaborative setting. In particular, we propose a trainable system for information distribution that will be able to support the dynamic nature of collaborative processes and provide users with task-relevant information. We expect that this will reduce problems due to information overload and will lead to more effective collaboration between all actors in the crisis management environment.
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Niels Netten, & Maarten Van Someren. (2008). Identifying segments for routing emergency response dialogues. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 108–117). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: In crisis management situations information is exchanged in different ways. In general, information is exchanged through spoken dialogues or text messaging conversations. Part of this exchanged dialogue information is often relevant to other actors involved in managing the crisis. Due to the dynamic character of the situation, dialogue partners may not be aware of who else needs the exchanged information. We present a coarse-grained segmentation method for automatically recognizing coherent dialogue segments which are then used for routing. We investigate the effectiveness of our features for recognizing boundaries of segments on transcribed emergency response dialogues and we compare classification by relevance of the identified information segments to the ideal topic segments.
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Niels Netten, & Maarten Van Someren. (2006). Automated support for dynamic information distribution in incident management. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 230–237). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: For all emergency response personnel involved in crisis situations it is essential to timely acquire all information critical to their task performance. However, in practice errors occur in the distribution of information between these collaborating actors leading to mistakes and subsequently more damage to the situation. In this paper we present a prototype system for dynamic information distribution able to support the information flow between collaborating crisis actors. The system has been evaluated by means of simulated experiments that use data from a real incident scenario. The results indicate that automated support by means of Machine Learning method works well. Especially, when actor work context features are included, then the performance on selecting and distributing relevant information is high. Furthermore, actors acquire relevant information much faster making group communication much more efficient.
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