An Algorithm for Ranking Hospitals based on Intuitionistic Fuzzy Sets and Sentiment Analysis
Jesus Serrano‐Guerrero, Mohammad Bani‐Doumi, Francisco P. Romero, José Á. Olivas · 2021
Understanding opinions about products offered by big online providers, for instance, TripAdvisor, is relatively easy because the features assessed by the user about hotels are well-known (food, room, desk, sleep quality, etc.). Nonetheless, in the health domain, many times the user provides free-text reviews which are not clearly focused on a few specific features. The present study proposes a methodology for recommending hospitals according to textual opinions which describe the quality of the offered services. First, it detects hospital aspects, which represent the hospital services, by a Latent Dirichlet Allocation-based approach following the criteria of a quality model called SERVQUAL. The polarity of those aspects is computed and modelled by intuitionistic fuzzy sets. Depending on the user preferences or his/her attitude, the aspects are aggregated to finally rank the alternative hospitals following a Multicriteria Decision Making algorithm (PROMETHEE II). The methodology has been tested using a large collection of free-text reviews on hospitals, which contain information about their offered services, obtaining interesting results.