Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
9-2015
Abstract
Product review mining is an important task that can benefit both businesses and consumers. Lately a number of models combining collaborative filtering and content analysis to model reviews have been proposed, among which the Hidden Factors as Topics (HFT) model is a notable one. In this work, we propose a new model on top of HFT to separate product properties and aspects. Product properties are intrinsic to certain products (e.g. types of cuisines of restaurants) whereas aspects are dimensions along which products in the same category can be compared (e.g. service quality of restaurants). Our proposed model explicitly separates the two types of latent factors but links both to product ratings. Experiments show that our proposed model is effective in separating product properties from aspects.
Discipline
Computer Sciences | Databases and Information Systems
Publication
Proceedings of Recent Advances in Natural Language Processing: 10th RANLP 2015: Hissar, Bulgaria, September 7-9 2015
First Page
131
Last Page
137
Publisher
ACL
City or Country
Stroudsburg, PA
Citation
DING YING and Jing JIANG.
A Joint Model of Product Properties, Aspects and Ratings for Online Reviews. (2015). Proceedings of Recent Advances in Natural Language Processing: 10th RANLP 2015: Hissar, Bulgaria, September 7-9 2015. 131-137.
Available at: https://ink.library.smu.edu.sg/sis_research/3073
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://aclweb.org/anthology/R/R15/R15-1019.pdf