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Evaluation of Recommender System
KTH, School of Technology and Health (STH), Medical Engineering, Computer and Electronic Engineering.
2016 (English)Independent thesis Basic level (professional degree), 10 credits / 15 HE creditsStudent thesisAlternative title
Utvärdering av rekommendationssystem (Swedish)
Abstract [en]

Recommender System (RS) has become one of the most important component for many companies, such as YouTube and Amazon. A recommender system consists of a series of algorithms which predict and recommend products to users. This report covers the selection of many open source recommender system projects, and movie predictions are made using the selected recommender system. Based on the predictions, a comparison was made between precision and an improved precision algorithm.

The selected RS uses singular value decomposition in the field of collaborative filtering. Based on the recommendation results produced by the RS, the comparison between precision and the improved precision algorithms showed that the result of improved precision is slightly higher than precision in different cutoff values and different dimensions of eigenvalues.

Abstract [sv]

Rekommendationssystem har blivit en av de viktigaste beståndsdelar för många företag, såsom YouTube och Amazon. Ett rekommendationssystem består av en serie av algoritmer som förutsäger och rekommenderar produkter till användare. Denna rapport omfattar valet av många öppen källkod rekommendationssystem projekt, och filmprognoser görs med det valda rekommendationssystemet. Baserat på filmprognoser, gjordes en jämförelse mellan precision och en förbättrad precision algoritmer.

Det valda rekommendationssystemet använder singulärvärdesuppdelning som kollaborativ filtrering. Baserat på rekommendationsresultat som produceras av rekommendationssystemet, jämförelsen mellan precision och den förbättrade precisions algoritmer visade att resultatet av förbättrad precision är något högre än precision i olika brytvärden och olika dimensioner av egenvärden.

Place, publisher, year, edition, pages
2016. , 42 p.
Series
TRITA-STH, 2016:51
Keyword [en]
Recommender system, singular value decomposition, precision, recommendation accuracy
Keyword [sv]
Rekommendationssystem, singulärvärdesuppdelning, precision, rekommendations noggrannhet
National Category
Computer Engineering
Identifiers
URN: urn:nbn:se:kth:diva-188529OAI: oai:DiVA.org:kth-188529DiVA: diva2:935982
External cooperation
PlayPilot
Subject / course
Computer Technology, Program- and System Development
Educational program
Bachelor of Science in Engineering - Computer Engineering
Supervisors
Examiners
Available from: 2016-09-29 Created: 2016-06-13 Last updated: 2016-09-29Bibliographically approved

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CiteExportLink to record
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Citation style
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Output format
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