Change search
Refine search result
1 - 1 of 1
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • 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
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Alinder, Helena
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Nilsson, Josefin
    KTH, School of Electrical Engineering and Computer Science (EECS).
    An Evaluation of the Indian Buffet Process as Part of a Recommendation System2018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

     This report investigates if it is possible to use the Indian Buffet Process (IBP), a stochastic process that defines a probability distribution, as part of a recommendation system. The report focuses on recommendation systems where one type of object, for instance movies, is recommended to another type of object, for instance users.        

    A concept of performing link prediction with IBP is presented, along with a method for performing inference. Three papers that are related to the subject are presented and their results are analyzed together with additional experiments on an implementation of the IBP.       

    The report arrives at the conclusion that it is possible to use IBP in a recommendation system when recommending one object to another. In order to use IBP priors in a recommendation system which include real-life datasets, the paper suggests the use of a coupled version of the IBP model and if possible perform inference with a parallel Gibbs sampling.

1 - 1 of 1
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • 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