Personalizing Product Rankings Using Collaborative Filtering on Opinion-Derived Topic Profiles

Musat, Claudiu Cristian; Faltings, Boi

Personalizing Product Rankings Using Collaborative Filtering on Opinion-Derived Topic Profiles

Download BibTeX Cite

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 830-835.

Abstract

Product review sites such as TripAdvisor, Yelp or Amazon provide a single, non personalized ranking of products. The sparse review data makes personalizing recommendations difficult. Topic Profile Collaborative Filtering exploits review texts to identify user profiles as a basis for similarity. We show that careful use of the available data and separating users into classes can greatly improve the performance of such techniques. We significantly improve MAE, RMSE, and Kendall tau, compared to the previous best results. In addition, we show that personalization does not benefit all the users to the same extent. We propose switching between a personalized and a non personalized method based on the user opinion profile. We show that the user's opinionatedness is a good indicator of whether the personalization will work or not.

Claudiu Cristian Musat, and Boi Faltings. 2015. Personalizing Product Rankings Using Collaborative Filtering on Opinion-Derived Topic Profiles. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15. IJCAI, 830–835. https://ijcai.org/proceedings/2015/122

@inproceedings{ijcai2015p122,
  title     = {Personalizing Product Rankings Using Collaborative Filtering on Opinion-Derived Topic Profiles},
  author    = {Musat, Claudiu Cristian and Faltings, Boi},
  booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
               Artificial Intelligence, {IJCAI-15}},
  publisher = {International Joint Conferences on Artificial Intelligence},
  editor    = {Qiang Yang and Michael Wooldridge},
  pages     = {830--835},
  year      = {2015},
  month     = {7},
  note      = {Main Track},
  url       = {https://ijcai.org/proceedings/2015/122},
}

TY  - CPAPER
TI  - Personalizing Product Rankings Using Collaborative Filtering on Opinion-Derived Topic Profiles
AU  - Musat, Claudiu Cristian
AU  - Faltings, Boi
T2  - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15
PB  - International Joint Conferences on Artificial Intelligence
PY  - 2015
SP  - 830
EP  - 835
UR  - https://ijcai.org/proceedings/2015/122
ER  -