Automatised analysis of emergency calls using Natural Language Processing

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dc.contributor.authorAndersson, Emarin
dc.contributor.authorEriksson, Benjamin
dc.contributor.authorHolmberg, Sofia
dc.contributor.authorHussain, Hossein
dc.contributor.authorJäberg, Lovisa
dc.contributor.authorThorsell, Erik
dc.contributor.departmentChalmers tekniska högskola / Institutionen för data- och informationsteknik (Chalmers)sv
dc.contributor.departmentChalmers University of Technology / Department of Computer Science and Engineering (Chalmers)en
dc.date.accessioned2019-07-03T14:21:52Z
dc.date.available2019-07-03T14:21:52Z
dc.date.issued2016
dc.description.abstractThe operators at SOS Alarm receives thousands of calls each day at the different emergency medical communication centres, owned by SOS Alarm, all over Sweden. A subset of these calls contain room for improvement and the operators could learn to improve from these calls. The work of finding – and analysing – these calls is however too tedious to be done by a human. This thesis presents four automatised solutions to this issue. The human factor is removed and the job of finding and analysing the calls is done by a computer. It is shown that it is possible to partly automatise the analysis, but the methods used have different strengths and weaknesses. Word frequency analysis is proven adequate at key word lookup. Similarity comparisons of various aspects of the calls are proven good at classifying calls, but less good at answering specific questions. Comparing parse trees seems promising, but the technology needs more work before it is ready to be used. The solutions presented show that it could be possible to automatise the analysis of the calls given that the right questions are asked and the results from these are used appropriately.
dc.identifier.urihttps://hdl.handle.net/20.500.12380/244534
dc.language.isoeng
dc.setspec.uppsokTechnology
dc.subjectInformations- och kommunikationsteknik
dc.subjectData- och informationsvetenskap
dc.subjectInformation & Communication Technology
dc.subjectComputer and Information Science
dc.titleAutomatised analysis of emergency calls using Natural Language Processing
dc.type.degreeExamensarbete för kandidatexamensv
dc.type.degreeBachelor Thesisen
dc.type.uppsokM2
local.programmeDatateknik 300 hp (civilingenjör)
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