Intelligent Database Systems Lab 國國國國國國國國 National Yunlin University of Science and Technology 1 TANGENT: A Novel, “Surprise-me”, Recommendation Algorithm Kensuke Onuma , Hanghang Tong , Christos Faloutsos 2009.SIGKDD Presented by Chien-Hao Kung 2011/8/10
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TANGENT : A Novel, “Surprise-me”, Recommendation Algorithm
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Intelligent Database Systems Lab
國立雲林科技大學National Yunlin University of Science and Technology
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TANGENT: A Novel, “Surprise-me”, Recommendation Algorithm
· Most of the recommendation algorithms focus on the precision in the proximity to user preferences. However, this strategy tends to suggest items only on the center of user preferences and thus narrows down the users’ horizons.
Intelligent Database Systems Lab
N.Y.U.S.T.
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Objectives
· To propose a method which are well connected to older choices, and at the same time well connected to unrelated choices.
· The method is carefully designed to be (a) parameter-free (b) effective and (c) fast.
Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Methodology
Define TANGENT problem as follows: Given: an edge-weighted undirected graph G with
adjacency matrix A, the set of query nodes Q=()1i<k. Find: a node that (1) is close enough to Q, and (2) has
high potential to reach other nodes.
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Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Methodology
Framework of TANGENT Algorithm Step1: Calculate relevance score (RS) of each node: Step2: Calculate Bridging Score (BRS) of each node: Step3:Compute the TANGENT score () by somehow
merging two criteria above.
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Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Methodology
Relevance Score (RS) It’s proposed to use random walk with restart.
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Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Methodology
Bridging Score (BRS)
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Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Methodology
TANGENT Score Method 1: To use linear combination.