{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T07:45:39Z","timestamp":1769845539459,"version":"3.49.0"},"reference-count":44,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2020,9,2]],"date-time":"2020-09-02T00:00:00Z","timestamp":1599004800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010661","name":"H2020","doi-asserted-by":"publisher","award":["Grant agreement ID: 833088"],"award-info":[{"award-number":["Grant agreement ID: 833088"]}],"id":[{"id":"10.13039\/100010661","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Applied Sciences"],"abstract":"<jats:p>This research is aimed at creating and presenting DisKnow, a data extraction system with the capability of filtering and abstracting tweets, to improve community resilience and decision-making in disaster scenarios. Nowadays most people act as human sensors, exposing detailed information regarding occurring disasters, in social media. Through a pipeline of natural language processing (NLP) tools for text processing, convolutional neural networks (CNNs) for classifying and extracting disasters, and knowledge graphs (KG) for presenting connected insights, it is possible to generate real-time visual information about such disasters and affected stakeholders, to better the crisis management process, by disseminating such information to both relevant authorities and population alike. DisKnow has proved to be on par with the state-of-the-art Disaster Extraction systems, and it contributes with a way to easily manage and present such happenings.<\/jats:p>","DOI":"10.3390\/app10176083","type":"journal-article","created":{"date-parts":[[2020,9,2]],"date-time":"2020-09-02T09:29:28Z","timestamp":1599038968000},"page":"6083","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["DisKnow: A Social-Driven Disaster Support Knowledge Extraction System"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3359-9780","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Bon\u00e9","sequence":"first","affiliation":[{"name":"Instituto Universit\u00e1rio de Lisboa (ISCTE-IUL), 1649-026 Lisbon, Portugal"},{"name":"INOV INESC Inova\u00e7\u00e3o\u2014Instituto de Novas Tecnologias, 1000-029 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6563-9858","authenticated-orcid":false,"given":"Mariana","family":"Dias","sequence":"additional","affiliation":[{"name":"Instituto Universit\u00e1rio de Lisboa (ISCTE-IUL), 1649-026 Lisbon, Portugal"},{"name":"INOV INESC Inova\u00e7\u00e3o\u2014Instituto de Novas Tecnologias, 1000-029 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6662-0806","authenticated-orcid":false,"given":"Jo\u00e3o C.","family":"Ferreira","sequence":"additional","affiliation":[{"name":"Instituto Universit\u00e1rio de Lisboa (ISCTE-IUL), 1649-026 Lisbon, Portugal"},{"name":"INOV INESC Inova\u00e7\u00e3o\u2014Instituto de Novas Tecnologias, 1000-029 Lisbon, Portugal"},{"name":"Information Sciences, Technologies and Architecture Research Center (ISTAR-IUL), 1649-026 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2058-693X","authenticated-orcid":false,"given":"Ricardo","family":"Ribeiro","sequence":"additional","affiliation":[{"name":"Instituto Universit\u00e1rio de Lisboa (ISCTE-IUL), 1649-026 Lisbon, Portugal"},{"name":"INESC-ID Lisboa, 1000-029 Lisbon, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2020,9,2]]},"reference":[{"key":"ref_1","unstructured":"Dilley, M., Chen, R.S., Deichmann, U., Lerner-Lam, A.L., and Arnold, M. 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