3 Search Results for "Vasardani, Maria"


Document
Short Paper
Qualitative Spatial Reasoning over Questions (Short Paper)

Authors: Mohammad Kazemi Beydokhti, Matt Duckham, Yaguang Tao, Maria Vasardani, and Amy Griffin

Published in: LIPIcs, Volume 240, 15th International Conference on Spatial Information Theory (COSIT 2022)


Abstract
Although geospatial question answering systems have received increasing attention in recent years, existing prototype systems struggle to properly answer qualitative spatial questions. In this work, we propose a unique framework for answering qualitative spatial questions, which comprises three main components: a geoparser that takes the input questions and extracts place semantic information from text, a reasoning system which is embedded with a crisp reasoner, and finally, answer extraction, which refines the solution space and generates final answers. We present an experimental design to evaluate our framework for point-based cardinal direction calculus (CDC) relations by developing an automated approach for generating three types of synthetic qualitative spatial questions. The initial evaluations of generated answers in our system are promising because a high proportion of answers were labelled correct.

Cite as

Mohammad Kazemi Beydokhti, Matt Duckham, Yaguang Tao, Maria Vasardani, and Amy Griffin. Qualitative Spatial Reasoning over Questions (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 18:1-18:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


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@InProceedings{beydokhti_et_al:LIPIcs.COSIT.2022.18,
  author =	{Beydokhti, Mohammad Kazemi and Duckham, Matt and Tao, Yaguang and Vasardani, Maria and Griffin, Amy},
  title =	{{Qualitative Spatial Reasoning over Questions}},
  booktitle =	{15th International Conference on Spatial Information Theory (COSIT 2022)},
  pages =	{18:1--18:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-257-0},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{240},
  editor =	{Ishikawa, Toru and Fabrikant, Sara Irina and Winter, Stephan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.18},
  URN =		{urn:nbn:de:0030-drops-169039},
  doi =		{10.4230/LIPIcs.COSIT.2022.18},
  annote =	{Keywords: Qualitative spatial reasoning, geospatial question answering, Qualitative spatial questions}
}
Document
Short Paper
Smartphone Usability for Emergency Evacuation Applications (Short Paper)

Authors: David Amores, Maria Vasardani, and Egemen Tanin

Published in: LIPIcs, Volume 142, 14th International Conference on Spatial Information Theory (COSIT 2019)


Abstract
Mobile phone ubiquity has allowed the implementation of a number of emergency-related evacuation aids. Yet, these applications still face a number of challenges in human-mobile interaction, namely: (1) lack of widely accepted mobile usability guidelines, (2) people’s limited cognitive capacity when using mobile phones under stress, and (3) difficulty recreating emergency scenarios as experiments for usability testing. This study is intended as an initial view into smartphone usability under emergency evacuations by compiling a list of experimental observations and setting the ground for future research in cognitively-informed spatial algorithms and app design.

Cite as

David Amores, Maria Vasardani, and Egemen Tanin. Smartphone Usability for Emergency Evacuation Applications (Short Paper). In 14th International Conference on Spatial Information Theory (COSIT 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 142, pp. 2:1-2:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


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@InProceedings{amores_et_al:LIPIcs.COSIT.2019.2,
  author =	{Amores, David and Vasardani, Maria and Tanin, Egemen},
  title =	{{Smartphone Usability for Emergency Evacuation Applications}},
  booktitle =	{14th International Conference on Spatial Information Theory (COSIT 2019)},
  pages =	{2:1--2:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-115-3},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{142},
  editor =	{Timpf, Sabine and Schlieder, Christoph and Kattenbeck, Markus and Ludwig, Bernd and Stewart, Kathleen},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2019.2},
  URN =		{urn:nbn:de:0030-drops-110947},
  doi =		{10.4230/LIPIcs.COSIT.2019.2},
  annote =	{Keywords: cognitive load, smartphone usability, ecological validity, emergency evacuation}
}
Document
Early Detection of Herding Behaviour during Emergency Evacuations

Authors: David Amores, Maria Vasardani, and Egemen Tanin

Published in: LIPIcs, Volume 114, 10th International Conference on Geographic Information Science (GIScience 2018)


Abstract
Social scientists have observed a number of irrational behaviours during emergency evacuations, caused by a range of possible cognitive biases. One such behaviour is herding - people following and trusting others to guide them, when they do not know where the nearest exit is. This behaviour may lead to safety under a knowledgeable leader, but can also lead to dead-ends. We present a method for the automatic early detection of herding behaviour to avoid suboptimal evacuations. The method comprises three steps: (i) people clusters identification during evacuation, (ii) collection of clusters' spatio-temporal information to extract features for describing cluster behaviour, and (iii) unsupervised learning classification of clusters' behaviour into 'benign' or 'harmful' herding. Results using a set of different detection scores show accuracies higher than baselines in identifying harmful behaviour; thus, laying the ground for timely irrational behaviour detection to increase the performance of emergency evacuation systems.

Cite as

David Amores, Maria Vasardani, and Egemen Tanin. Early Detection of Herding Behaviour during Emergency Evacuations. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 1:1-1:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)


Copy BibTex To Clipboard

@InProceedings{amores_et_al:LIPIcs.GISCIENCE.2018.1,
  author =	{Amores, David and Vasardani, Maria and Tanin, Egemen},
  title =	{{Early Detection of Herding Behaviour during Emergency Evacuations}},
  booktitle =	{10th International Conference on Geographic Information Science (GIScience 2018)},
  pages =	{1:1--1:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Winter, Stephan and Griffin, Amy and Sester, Monika},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.1},
  URN =		{urn:nbn:de:0030-drops-93293},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.1},
  annote =	{Keywords: spatio-temporal data, emergency evacuations, herding behaviour}
}
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