Publication Type

Conference Proceeding Article

Publication Date



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.


Computer Sciences | Databases and Information Systems

Research Areas

Data Management and Analytics


Proceedings of Recent Advances in Natural Language Processing: 10th RANLP 2015: Hissar, Bulgaria, September 7-9 2015

First Page


Last Page




City or Country

Stroudsburg, PA

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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