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Meven: An Enterprise Trust Recommender System
KTH, School of Information and Communication Technology (ICT).
KTH, School of Information and Communication Technology (ICT).
2013 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Growing an online community takes time and effort. Relationships in an online community must be initiated based on trust followed by privacy, and then carefully cultivated. People are using web based social networks more than recent past, but they always want to protect their private data from unknown access; meanwhile also eager to know more people whom they are interested. Among all other system, trust based recommenders have been one of the most used and demanding system which takes the advantage of social trust to generate more accurate predictions. In this work we have proposed for Meven (An Enterprise trust-based profile recommendation with privacy), which uses Social Network Content (User Profiles and trends) with Trust and privacy control policy. The idea of system is to provide Social Networks with the ability to quickly find related information about the users having similar behaviors as the current user. The users will also be able to set the privacy metrics on their profiles so they will not get recommendation of those they feel less important and this is achieved by Privacy metrics. To generate accurate predictions, we defined trust between two users as a strong bond which is computed using different metrics based on user’s activities with respect to different content such as blogging, writing articles, commenting, and liking along with profile information such as organization, region, interests or skills. We have also introduced privacy metric in such a way so that users have full freedom to hide themselves from the recommendation system or they can also have the opportunity to customize their profiles to be visible to certain level of trustworthy users. We have exposed our application as a web service(api) so that any social network web portal can access the recommendations and publish them as a widget in social network.

Place, publisher, year, edition, pages
2013. , 70 p.
Series
Trita-ICT-EX, 2013:279
Keyword [en]
Recommender System, Trust Network, Social Network, Recommendation, Privacy protocol, Enterprise application
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-137737OAI: oai:DiVA.org:kth-137737DiVA: diva2:679659
Examiners
Available from: 2013-12-17 Created: 2013-12-16 Last updated: 2013-12-17Bibliographically approved

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CiteExportLink to record
Permanent link

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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
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  • rtf