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Ranking System based on Social Network of Domain Experts Mateusz Marmołowski May 28, 2008
Motivation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Our goals ,[object Object],[object Object],[object Object],[object Object],[object Object]
Rating Algorithm - agenda ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Rating Algorithm
Rating Calculation
RC – Friendship influence Range: [50 – 100%]
RC – Domain knowledge ,[object Object],[object Object],[object Object],[object Object],[object Object]
RC – Multiple domains ,[object Object],[object Object],[object Object],39% 5 47% 4 58% 3 75% 2 100% 1 MD(d) d
RC – User Weight ,[object Object],[object Object],[object Object],[object Object]
RC – Weighted Rate ,[object Object],[object Object],[object Object],[object Object],[object Object]
RC – Bayesian Weighted Rate - The average number of votes of all resources - The average rating of all resources’ ratings - The number of votes for this resource - The rating of this resource Final   formula:
Expertise Calculation
EC – Weighted Expertise Value ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
EC – Final expertise calculation ,[object Object],[object Object],[object Object],[object Object]
Expertise propagation
Expertise propagation – step 1
Expertise propagation – step 2
Expertise propagation – step 3
Summary ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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Real-life Rating Algorithm