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Author (up) Aladdin Shamoug; Stephen Cranefield; Grant Dick pdf 
  Title Information Retrieval for Humanitarian Crises via a Semantically Classified Word Embedding Type Conference Article
  Year 2018 Publication Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. Abbreviated Journal Iscram Ap 2018  
  Volume Issue Pages 132-144  
  Keywords Ontologies, Word Embedding, Information Retrieval, Humanitarian Crisis, Humanitarian Response.  
  Abstract Decision-makers in humanitarian crisis need information to guide them in making critical decisions. Finding information in such environments is a challenging task. Therefore, decision-makers rely on domain experts who possess experience and knowledge from previous humanitarian crises to provide them with the information they need. In this paper, we explore the ability of the existing computing technologies to augment the capabilities of those experts and help decision-makers to make faster and better decisions. Among many computing technologies we have today, word embedding and the semantic web are able to support such augmentation of the domain expert. In this paper, we train a word embedding model using word2vec, transform words and terms from news archive to entities in domain ontology, annotate those entities with their equivalent concepts from upper ontologies, and reason about them using semantic similarity and semantic matching, to represent and retrieve knowledge, and answer questions of interest to decision-makers in humanitarian crises. The approach was evaluated by comparing the use of word embeddings with and without semantic classification for the retrieval of information about the current humanitarian crisis in Syria.  
  Address University of Otago; University of Otago; University of Otago  
  Corporate Author Thesis  
  Publisher Massey Univeristy Place of Publication Albany, Auckland, New Zealand Editor Kristin Stock; Deborah Bunker  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-0-473-45447-0 Medium  
  Track Data Issues for Situation/Disaster Awareness Expedition Conference ISCRAM Asia Pacific 2018: Innovating for Resilience - 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific  
  Notes aladdin.shamoug@postgrad.otago.ac.nz Approved no  
  Call Number Serial 1679  
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