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Distributed Trust-Aware Recommender Systems
KTH, School of Information and Communication Technology (ICT).
2012 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Collaborative filtering(CF) recommender systems are among the most popular approaches to solving the information overload problem in social networks by generating accurate predictions based on the ratings of similar users. Traditional CF recommenders suffer from lack of scalability while decentralized CF recommenders (DHT based, gossip based etc.) have promised to alleviate this problem. Thus, in this thesis we propose a decentralized approach to CF recommender systems that uses the T-Man algorithm to create and maintain an overlay network that in turn would facilitate the generation of recommendations based on local information of a node. We analyze the influence of the number of rounds and neighbors on the accuracy of prediction and item coverage and we propose a new approach to inferring trust values between a user and its neighbors. Our experiments on three important datasets show an improvement of prediction accuracy relative to previous approaches while using a highly scalable, decentralized paradigm. We also analyze item coverage and show that our system is able to generate predictions for significant fraction of the users, which is comparable with the centralized approaches.

Place, publisher, year, edition, pages
2012. , 50 p.
Series
Trita-ICT-EX, 2012:283
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-108326OAI: oai:DiVA.org:kth-108326DiVA: diva2:579962
Educational program
Master of Science - Software Engineering of Distributed Systems
Uppsok
Technology
Examiners
Available from: 2013-01-02 Created: 2012-12-20 Last updated: 2013-01-02Bibliographically approved

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CiteExportLink to record
Permanent link

Direct 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