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dc.contributor.authorSekkingstad, Andreas
dc.date.accessioned2017-03-24T11:41:55Z
dc.date.available2017-03-24T11:41:55Z
dc.date.issued2016-12-01
dc.date.submitted2016-12-01eng
dc.identifier.urihttp://hdl.handle.net/1956/15606
dc.description.abstractThis master thesis investigated automatic methods of Word Sense Disambiguation (WSD) in HTML pages. The hypothesis was that HTML documents provide various disambiguation cues which are not normally present in general text, and which can enhance the quality of WSD. We tested several existing natural language processing toolkits which provide general WSD services, and compared these to our novel algorithms which were designed to take advantage of the HTML cues. The findings showed that our new algorithms outperformed state of the art general WSD implementations. In addition, our algorithm could provide a ranked list of potential disambiguations, which is useful in an example use case where users “tag” key words in a web page with the help of the disambiguating algorithm.en_US
dc.format.extent1143674 byteseng
dc.format.mimetypeapplication/pdfeng
dc.language.isoengeng
dc.publisherThe University of Bergeneng
dc.subjectWSDeng
dc.subjectsemantic webeng
dc.subjectsemantikkeng
dc.subjectnlpeng
dc.subjectWordneteng
dc.titleWord sense disambiguation in webpages. Developing a program capable to disambiguate words with a website text as contexteng
dc.typeMaster thesisen_US
dc.rights.holderCopyright the author. All rights reserved.en_US
dc.description.localcodeINFO390
dc.description.localcodeMASV-INFO
dc.subject.nus735115eng
fs.subjectcodeINFO390


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