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Author Zoha Sheikh; Hira Masood; Sharifullah Khan; Muhammad Imran pdf 
  Title User-Assisted Information Extraction from Twitter During Emergencies 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 684-691  
  Keywords social media; disaster response; query expansion; supervised learning  
  Abstract Disasters and emergencies bring uncertain situations. People involved in such situations look for quick answers to their rapid queries. Moreover, humanitarian organizations look for situational awareness information to launch relief operations. Existing studies show the usefulness of social media content during crisis situations. However, despite advances in information retrieval and text processing techniques, access to relevant information on Twitter is still a challenging task. In this paper, we propose a novel approach to provide timely access to the relevant information on Twitter. Specifically, we employee Word2vec embeddings to expand initial users queries and based on a relevance feedback mechanism we retrieve relevant messages on Twitter in real-time. Initial experiments and user studies performed using a real world disaster dataset show the significance of the proposed approach.  
  Address National University of Sciences and Technology, Islamabad, Pakistan; Qatar Computing Research Institute, HBKU Doha, Qatar  
  Corporate Author Thesis  
  Publisher Place of Publication Albi, France Editor Tina Comes, Frédérick Bénaben, Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title (up)  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN Medium  
  Track Social Media Studies Expedition Conference 14th International Conference on Information Systems for Crisis Response And Management  
  Notes Approved no  
  Call Number Serial 1502  
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