Hotel Recommendation System Based on User Profiles and Collaborative Filtering

Turker, Bekir Berker; Tugay, Resul; Kızıl, İpek; Öğüdücü, Şule Gündüz

doi:10.1109/ubmk.2019.8907093

Cited by 5 publications

(3 citation statements)

References 28 publications

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“…32 Collaborative filtering-based methods are still the mainstream of research in this field. 9,14,15 However, there are privacy issues with this type of method because travelers may not understand how their browsing history and messages on social networks are analyzed. 33 The outbreak of COVID-19 and the ensuing city lockdowns have severely affected hotels around the world.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In the literature, a number of methods for recommending hotels have been proposed, for example, weighted average (WA) or fuzzy-WA (FWA), 4 – 8 analytic hierarchy process (AHP) or fuzzy AHP, 9 , 10 adaptive neuro-fuzzy inference systems (ANFISs), 11 RankBoost algorithms, 12 text mining, 13 collaborative filtering, 9 , 14 – 16 etc. There are also websites (e.g.…”

Section: Introductionmentioning

confidence: 99%

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A fuzzy analytic hierarchy process-enhanced fuzzy geometric mean-fuzzy technique for order preference by similarity to ideal solution approach for suitable hotel recommendation amid the COVID-19 pandemic

Chen

Hsu

2022

DIGITAL HEALTH

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Cities around the world have reopened from the lockdown caused by the COVID-19 pandemic, and more and more people are planning regional travel. Therefore, it is a practical problem to recommend suitable hotels to travelers amid the COVID-19 pandemic. However, it is also a challenging task since the critical factors that affect hotel selection amid the COVID-19 pandemic may be different from those usually considered. From this perspective, the fuzzy analytic hierarchy process-enhanced fuzzy geometric mean-fuzzy technique for order preference by similarity to ideal solution approach is proposed in this study for hotel recommendation. The proposed methodology not only considers the critical factors affecting hotel selection amid the COVID-19 pandemic, but also establishes a systematic mechanism, that is, enhanced fuzzy geometric mean, to simultaneously improve the accuracy and efficiency of the recommendation process. The fuzzy analytic hierarchy process-enhanced fuzzy geometric mean-fuzzy technique for order preference by similarity to ideal solution approach has been successfully applied to recommend suitable hotels to 10 travelers for regional trips amid the COVID-19 pandemic.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A fuzzy analytic hierarchy process-enhanced fuzzy geometric mean-fuzzy technique for order preference by similarity to ideal solution approach for suitable hotel recommendation amid the COVID-19 pandemic

Chen

Hsu

2022

DIGITAL HEALTH

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“…In addition, due to the wealth of information available in online reservation systems, customers may miss out on a more suitable option for them. In this sense, recommendation systems play a major role in customers' choices [22].Recommendation systems are useful for service providers and users [5]. They decrease transaction costs for finding and choosing products in an online shopping environment [6].…”

Section: Introductionmentioning

confidence: 99%

A Manhattan distance based hybrid recommendation system

UYANIK>

Orman

2023

International Journal of Applied Mathematics Electronics and Computers

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Many online service providers use a recommendation system to assist their customers' decision-making by generating recommendations. Accordingly, this paper proposes a new recommendation system for tourism customers to make online reservations for hotels with the features they need, saving customers time and increasing the impact of personalized hotel recommendations. This new system combined collaborative and content-based filtering approaches and created a new hybrid recommendation system. Two datasets containing customer information and hotel features were analyzed by Recency, Frequency, Monetary (RFM) method in order to identify customers according to their purchasing nature. The main idea of the recommendation system is to establish correlations between users and products and make the decision to choose the most suitable product or information for a particular user. As a result of the exponential growth of online data, this vast amount of information for use in the tourism industry can be leveraged by decision-makers to make purchasing decisions[20]. Filtering, prioritizing, and beneficially presenting relevant information reduces this overload. There are following three main ways that recommendation systems can generate a recommendation list for a user; content-based, collaborative-based, and hybrid approaches[1]. This paper describes each category and its techniques in detail. RFM Analysis is used to identify customer segments by measuring customers' purchasing habits. It is the process of labeling customers by determining the Recency, Frequency, and Monetary values of their purchases and ranking them on a scoring model. Scoring is based on how recently they bought (Recency), how often they bought (Frequency), and purchase size (Monetary). Experimental results show that the accuracy of behavior analysis using Manhattan distance-based hybrid filtering is greatly improved compared to collaborative and content-based algorithms.

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Recommending suitable hotels to travelers in the post-COVID-19 pandemic using a novel FAHP-fuzzy TOPSIS approach

Chen,

Wu,

Hsu

2024

Complex Intell. Syst.

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Cities around the world have reopened from the lockdown caused by the COVID-19 pandemic, and more and more people are planning regional travel. Therefore, it is a practical problem to recommend suitable hotels to travelers amid the COVID-19 pandemic. However, it is also a challenging task since the criteria that affect hotel selection amid the COVID-19 pandemic may be different from those usually considered. From this perspective, a novel fuzzy analytic hierarchy process (FAHP)-fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS) approach is proposed in this study for hotel recommendation. The proposed methodology not only considers the criteria affecting hotel selection amid the COVID-19 pandemic, but also establishes a systematic mechanism to simultaneously improve the accuracy and efficiency of the recommendation process. The novel FAHP-fuzzy TOPSIS approach has been successfully applied to recommend suitable hotels to fifteen travelers for regional trips amid the COVID-19 pandemic.

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Hotel Recommendation System Based on User Profiles and Collaborative Filtering

Cited by 5 publications

References 28 publications

A fuzzy analytic hierarchy process-enhanced fuzzy geometric mean-fuzzy technique for order preference by similarity to ideal solution approach for suitable hotel recommendation amid the COVID-19 pandemic

A fuzzy analytic hierarchy process-enhanced fuzzy geometric mean-fuzzy technique for order preference by similarity to ideal solution approach for suitable hotel recommendation amid the COVID-19 pandemic

A Manhattan distance based hybrid recommendation system

Recommending suitable hotels to travelers in the post-COVID-19 pandemic using a novel FAHP-fuzzy TOPSIS approach

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