Search engines are as important as recommender systems for hotel selections. However, the recommended lists of search engines are usually non-personalized and low accuracy. In order to deal with these issues in search engines, a comprehensive mechanism for hotel recommendation is proposed. In this mechanism, we consider users' personalized preferences by identifying users' attributes about interest, trust and consumption capacity. Meanwhile, the quantification method for each attribute is

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... ted by using fuzzy theory. Moreover, this paper improves the method to evaluate the hotel, which respects to the criteria price, rating, and online review by using fuzzy theory. In addition, this proposed approach uses TOPSIS, a classical multi-criteria decision making method, to improve the accuracy further. Finally, a case study is conducted based on Tripadvisor.com to illustrate the validity of the proposed method for hotel recommendation in search engines. The results of the case study indicate that it not only solves the problem of non-personalization, but also improves the accuracy in search engine.