Social Network-Based Recommender Systems by Schall Daniel

Author:Schall, Daniel
Language: eng
Format: epub, azw3
Publisher: Springer International Publishing
Published: 2015-09-22T16:00:00+00:00

(4.2)

(4.3)

This adjusted model is a natural way of designing a random-walk based algorithm following the HITS model. The randomized HITS approach is, like PageRank, stable to small perturbations [32]. The symbols δ O (o) and δ P (p) depict personalization vectors that may be assigned uniformly for each node such that and . Non-uniform personalization vectors result in personalized rankings. The parameters and with allow for balancing between authority/hub weights and personalization weights. A typical value for λ is 0.85 [9]. Assigning lower values to λ means that higher importance is given to the personalization weights; thereby reducing the “network effect” of the ranking algorithm.

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