Change search
CiteExportLink to record
Permanent link

Direct link
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
Towards a new generation of movie recommender systems: A mood based approach
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Informatics and Media, Information Systems.
2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The emergence of the content overloaded internet creates a lot of new challengesfor users and service providers a like. To minimize the displayed amount of contentlike movies, music, or other products service providers like Netflix or Amazonare using recommender systems which aim to guide the user trough the availableinformation. These systems collect knowledge about the user and try to deliver personalized experiences. Most of the state-of-the-art recommender systems are using acontent focused approach but often fail to grasp the nature of users’ desires. Therefore,a mood-as-input model is developed which combines the existing research onhuman mood identification and the emotion classification of content in the domainof movies. In order to match these two components different machine learning modelsare evaluated and a Random Forest is selected as the main matching algorithm.The results of this study indicate that the mood of a user can be used to create personalizedcontent recommendations and that it can perform better than an Arbitrarysystem.

Place, publisher, year, edition, pages
2018. , p. 71
Keywords [en]
Recommender Systems, Machine Learning, Mood
National Category
Interaction Technologies
Identifiers
URN: urn:nbn:se:uu:diva-353805OAI: oai:DiVA.org:uu-353805DiVA, id: diva2:1219240
Educational program
Master programme in Information Systems
Available from: 2018-06-19 Created: 2018-06-15 Last updated: 2018-06-19Bibliographically approved

Open Access in DiVA

fulltext(3247 kB)4 downloads
File information
File name FULLTEXT01.pdfFile size 3247 kBChecksum SHA-512
93253178d97c1e1dadb841099cf9f159397d317ba5ef7da367000909857167b15059f702ddeeff3de0a512b9bbce469488b1051d2daacd63d8ea4da203f28bdb
Type fulltextMimetype application/pdf

By organisation
Information Systems
Interaction Technologies

Search outside of DiVA

GoogleGoogle Scholar
Total: 4 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 73 hits
CiteExportLink to record
Permanent link

Direct link
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