Recommending social platform content using deep learning

dc.contributor.authorGoretskyy, Maxim
dc.contributor.authorHåkansson, Alexander
dc.contributor.authorJaxing, Jesper
dc.contributor.authorAlmén, Jonatan
dc.contributor.authorOlivecrona, Axel
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.accessioned2019-07-03T14:36:08Z
dc.date.available2019-07-03T14:36:08Z
dc.date.issued2017
dc.description.abstractIn this thesis a model based on artificial neural networks, seeing how they have found successes in a variety of fields in recent years, is proposed as an alternative to existing recommender systems. A recurrent neural network model is built for recommending content to users on the social forum Reddit based on the titles of posts. The model is compared against Facebook’s fastText classifier and a model based on N-grams. The model proposed is performing close to, but not as well as either fastText or the N-grams based model. The model does not show any real advantages in its current state but a lot of potential improvements are proposed.
dc.identifier.urihttps://hdl.handle.net/20.500.12380/251698
dc.language.isoeng
dc.setspec.uppsokTechnology
dc.subjectData- och informationsvetenskap
dc.subjectComputer and Information Science
dc.titleRecommending social platform content using deep learning
dc.type.degreeExamensarbete för kandidatexamensv
dc.type.degreeBachelor Thesisen
dc.type.uppsokM2
local.programmeDatateknik 300 hp (civilingenjör)

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