Season-aware attraction recommendation method with dual-trust enhancement

Huang, Chao, Liu, Mengying, Gong, Huiqun and Xu, Faye (2017) Season-aware attraction recommendation method with dual-trust enhancement. Journal of Intelligent & Fuzzy Systems, 33 (4). pp. 2437-2449. ISSN 1064-1246

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Attraction recommendation plays an essential role in tourism. For example, it can relieve information overload for tourists and increase sales for tourism operators. When making travel decisions, tourists depend heavily on the personal preferences and suggestions from people they trust. However, most existing attraction recommendation methods focus on the tourist preferences for topics of attractions, yet overlook the seasonality in topic preferences. Additionally, extant studies are generally based on a single type of trust, which may represent trust relations inaccurately. In order to overcome these issues, we propose a novel season-aware attraction recommendation method based on the seasonal topic preferences and dual-trust relations. Firstly, we capture tourists’ seasonal topic preferences by analyzing their travel histories along two dimensions: time and attraction. Secondly, we develop a dual-trust relationship (DTR) model based on familiarity-based trust and similarity-based trust, in contrast to existing studies that purely focus on a single type of trust. Thirdly, we propose a novel season-aware attraction recommendation method named SAR-DTR. In a specific season, it predicts ratings based on both topic preferences in the given season and suggestions from tourists they trust. To demonstrate the superiority of the proposed method to other approaches, an empirical study with real-world data was conducted. The experimental results regarding both prediction and recommendation performance are reported.

Item Type: Article
Identifier: 10.3233/jifs-17569
Additional Information: Copyright © IOS Press and the authors. Non-commercial use only. The final published version of this article can be accessed online at
Keywords: Attraction recommendation, seasonal topic preference, similarity-based trust, familiarity-based trust
Subjects: Computing > Information management
Hospitality and tourism > Tourism
Related URLs:
Depositing User: Faye Xu
Date Deposited: 18 Jun 2020 10:00
Last Modified: 28 Aug 2021 07:13


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