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An Enterprise Social Recommendation System for Connecting Swedish Professionals
KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.ORCID iD: 0000-0002-4722-0823
KTH, School of Information and Communication Technology (ICT).
KTH, School of Information and Communication Technology (ICT).
2014 (English)In: Proceedings - IEEE 38th Annual International Computers, Software and Applications Conference Workshops, COMPSACW 2014 / [ed] Carl K. Chang, Yan Gao, Ali Hurson, Mihhail Matskin, Bruce McMillin, Yasuo Okabe, IEEE Communications Society, 2014, 234-239 p.Conference paper, Published paper (Refereed)
Abstract [en]

Most cooperative businesses rely on some form of social networking system to facilitate user profiling and networking of their employees. To facilitate the discovery, matchmaking and networking among the co-workers across the enterprises social recommendation systems are often used. Off-the-shelf nature of these components often makes it hard for individuals to control their exposure as well as their preferences of whom to connect to. To this end, trust based recommenders have been amongst the most popular and demanding solutions due to their advantage of using social trust to generate more accurate suggestions for peers to connect to. They also allow individuals to control their exposure based on explicit trust levels. In this work we have proposed for an enterprise trust-based recommendation system with privacy controls. To generate accurate predictions, a local trust metric is defined between users based on correlations of user's profiled content such as blogging, articles wrote, comments, and likes along with profile information such as organization, region, interests or skills. Privacy metric is defined in such a way that users have full freedom either to hide their data from the recommender or customize their profiles to make them visible only to users with defined level of trustworthy.

Place, publisher, year, edition, pages
IEEE Communications Society, 2014. 234-239 p.
Keyword [en]
social recommender systems, recommender systems, social networks, trust, privacy, social matching
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-160457DOI: 10.1109/COMPSACW.2014.42ISI: 000352787700040Scopus ID: 2-s2.0-84931025177ISBN: 978-1-4799-3578-9 (print)OAI: oai:DiVA.org:kth-160457DiVA: diva2:789656
Conference
38th Annual IEEE Computer Software and Applications Conference Workshops, COMPSACW 2014, Vasteras, Sweden, 27 July 2014 through 29 July 2014
Note

QC 20150223

Available from: 2015-02-19 Created: 2015-02-19 Last updated: 2015-08-05Bibliographically approved

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Matskin, Mihhail

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Dokoohaki, NimaMatskin, MihhailAfzal, UsmanIslam, Md. Mistamikul
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