Change search
ReferencesLink to record
Permanent link

Direct link
Evaluation of label incorporated recommender systems: Based on restricted boltzmann machines
University of Skövde, School of Informatics.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

In this thesis the problem of providing good recommendations to assist users to make the best choice out of numerous options is studied. To overcome the common problem of sparsity of the data, from which recommendations are inferred, additional label information assigned to items is considered. Based on a literature survey approaches that have proven to perform well were identified and combined into a single Framework. The proposed framework is based on the third-order Restricted Boltzmann machine which enables to incorporate label information as well as traditional rating information into a single model. The framework also implements the global-approach of collaborative filtering, where the user- and item-based approaches are both considered to improve the performance of the model. The proposed framework is implemented and evaluated using an experiment measuring the prediction error on test samples. The results obtained from the conducted experiments did not confirm the assumptions made about the improve of the models accuracy, when incorporating the additional label information. Reasons for this are identified and discussed.

Place, publisher, year, edition, pages
2016. , 31 p.
National Category
Computer Science
URN: urn:nbn:se:his:diva-12609OAI: diva2:943443
Subject / course
Educational program
Data Science - Master’s Programme
Available from: 2016-06-30 Created: 2016-06-27 Last updated: 2016-06-30Bibliographically approved

Open Access in DiVA

fulltext(1314 kB)33 downloads
File information
File name FULLTEXT01.pdfFile size 1314 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Huhnstock, Nikolas
By organisation
School of Informatics
Computer Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 33 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

Total: 125 hits
ReferencesLink to record
Permanent link

Direct link