An extended recommendation system by applying aspect-based sentiment analysis method on customers' review and experience
by Thanh Ho; An-Dinh Van; Trinh Tran Thi Kieu; Anh Nguyen Thi Linh; Thao Huynh Nhi Thanh; Hieu Tran Nguyen Ngoc
International Journal of Intelligent Information and Database Systems (IJIIDS), Vol. 16, No. 4, 2024

Abstract: The hotel industry heavily relies on customer reviews and recommendations to attract guests and ensure customer satisfaction. However, the abundance of online reviews poses a challenge for users seeking relevant and reliable information for their hotel selection process. This study proposes a novel approach that leverages aspect-based sentiment analysis (ABSA) to assess the alignment between hotel sentiment scores and user preferences at the aspect level. By experimenting on 62,887 customer feedback in hospitality industry, two approaches are developed and presented: 1 calculating aspect-based sentiment hotel profiles using Wu-Palmer similarity, predefined index terms, and PyABSA; 2) extracting user preferences through term frequency (TF). The recommendation results are obtained by aligning hotel sentiment scores with user preferences using a value-focused approach (scalar product). Our evaluation, based on the Mean Reciprocal Rank (MRR) metric, reveals that, the most suitable hotel is within the top 5 recommended items, with an MRR value of 0.2849.

Online publication date: Tue, 01-Oct-2024

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