An Approach for Reducing the Numeric Rating Bias
- https://doi.org/10.2991/icitel-15.2016.11How to use a DOI?
- bias; evaluation; review mining; e-business
There is bias in customer reviews and the associated ratings. We propose a method to identify and reduce such bias on the part of reviewers. There are three phases in our approach. Firstly, we conduct Rating-aware sentiment analysis for each review text accompanied with the numeric ratings. Then, we extract features of review text and do manual labelling for training learning machine. At last, SVM is used to train the learner to reduce the rating bias. We applied our method on the dataset obtained from amazon.com. Results suggest that biased ratings have effects on customer ratings significantly in recommender systems and that this bias can be substantially reduced by our model.
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Xiu Li AU - Huimin Wang AU - Jian Xu PY - 2016/03 DA - 2016/03 TI - An Approach for Reducing the Numeric Rating Bias BT - Proceedings of the 1st International Conference on Information Technologies in Education and Learning PB - Atlantis Press SP - 48 EP - 53 SN - 2352-538X UR - https://doi.org/10.2991/icitel-15.2016.11 DO - https://doi.org/10.2991/icitel-15.2016.11 ID - Li2016/03 ER -