Abstract
Online reviews suffer from certain reliability problems such as lack of reviewer objectivity, reviewer bias, lack of domain familiarity on the part of the reviewer, etc. This disclosure describes techniques to improve the reliability of review scores obtained from online review facilities. A set of meta-parameters, referred to as review reliability parameters (RRP), is defined and associated with the underlying numerical rating of a review. RRPs are inputs to a machine learning model that derives a weighted review. The review of a reviewer with good RRPs is weighted more than the review of a reviewer with poor RRPs. RRPs can be based on factors such as the reviewer’s domain-specific expertise, history, demographic, meta-reviews, reviewing experience, etc. The techniques enable the creation of reliable, normalized reviews.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Ventura, Alexander and Lavery, Andy, "Reliable Normalized Customer Reviews", Technical Disclosure Commons, (November 15, 2021)
https://www.tdcommons.org/dpubs_series/4700