Tracking temporal evolution in word meaning with distributed word representations

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dc.contributor.authorAlburg, Henrik
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.accessioned2019-07-03T13:51:51Z
dc.date.available2019-07-03T13:51:51Z
dc.date.issued2015
dc.description.abstractSome words change meaning over time and are thus used differently in text. The purpose of this thesis is to create a model able to find these changes in word meaning, by studying lots of data from different time periods. Building on recent advancements in machine learning and semantic modelling the model is successfully able to find and make sense of changes in word meaning over time. The model can automatically find the most changed words during a time span and these words tend to agree with our perception of the words that have changed the most. When measuring changes the model achieves a 0.6 correlation when compared to human raters.
dc.identifier.urihttps://hdl.handle.net/20.500.12380/228927
dc.language.isoeng
dc.setspec.uppsokTechnology
dc.subjectInformations- och kommunikationsteknik
dc.subjectData- och informationsvetenskap
dc.subjectInformation & Communication Technology
dc.subjectComputer and Information Science
dc.titleTracking temporal evolution in word meaning with distributed word representations
dc.type.degreeExamensarbete för masterexamensv
dc.type.degreeMaster Thesisen
dc.type.uppsokH
local.programmeComputer science – algorithms, languages and logic (MPALG), MSc
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