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Optimize Ranking System With Machine Learning
Halmstad University, School of Information Technology.
Halmstad University, School of Information Technology.
2018 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

This thesis investigates how recommendation systems has been used and can be used with the help of different machine learning algorithms. Algorithms used and presented are decision tree, random forest and singular-value decomposition(SVD). Together with Tingstad, we have tried to implement the SVD function on their recommendation engine in order to enhance the recommendation given. A trivial presentation on how the algorithms work. General information about machine learning and how we tried to implement it with Tingstad’s data. Implementations with Netflix’s and Movielens open-source dataset was done, estimated with RMSE and MAE.

Place, publisher, year, edition, pages
2018. , p. 37
Keywords [en]
ML, B2B, Machine learning, SVD, Decision tree
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:hh:diva-37431OAI: oai:DiVA.org:hh-37431DiVA, id: diva2:1229565
External cooperation
Tingstad; 3Bits AB
Educational program
Computer Science and Engineering, 300 credits
Supervisors
Examiners
Available from: 2018-07-02 Created: 2018-07-01 Last updated: 2018-07-02Bibliographically approved

Open Access in DiVA

fulltext(558 kB)30 downloads
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File name FULLTEXT02.pdfFile size 558 kBChecksum SHA-512
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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf