Opinion mining (also known as sentiment analysis) through customers’
reviews or feedbacks which can identify the user opinion about different product
features has received a lot of attention exhibited in numerous studies. The majority
of recommender systems have recommended products based only on overall evaluation
and primarily based on expert’s evaluation. In this work, we propose a method
to explore Vietnamese reviews extracted from e-commerce websites in Vietnam
to provide suggestions in products selection based on products’ features/functions.
The proposed approach introduces a topic-based model to identify products’ features
which are mentioned in customer comments/reviews. The proposed system
is implemented with the integration combining the VietSentiWordnet to calculate
the importance scores for the features of each product. We also construct a product
recommendation database which can store customers preference and purchases history.
The work is analysed on more than 2,000 Vietnamese comments/reviews about
laptop products and is expected to be feasible to apply in practical cases.