Making recommendations in Social Networks based on textual reviews: a confidence-based approach (version 2.0)

Dionisis Margaris, Costas Vassilakis, Dimitris Spiliotopoulos

SoDa Technical report TR-19002v2

Note: this version extends and supersedes the first version of the report, which is available here.

Abstract:
In this technical report, we present the experimental findings from applying an algorithm that (1) considers the characteristics of Social Networks (SNs) user reviews which affect the review-to-rating conversion procedure, (2) computes a confidence level for each rating, which reflects the uncertainty level for each conversion process and (3) exploit this metric both in the users’ similarity computation and in the prediction formulation phases in recommender systems.
More specifically, we evaluate the performance of the proposed approach in terms of (i) SN users’ satisfaction and (ii) precision, regarding the recommendations formulated based on the rating predictions generated by the proposed algorithm.

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