An online review-driven two-stage hotel recommendation model considering customers’ risk attitudes and personalized preferences

IF 6.7 2区 管理学 Q1 MANAGEMENT
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引用次数: 0

Abstract

Hotel recommendation models provide crucial references for customers to select their ideal hotels and help them overcome information overload. However, previous models primarily focus on capturing public preferences, neglecting personalized preferences or different risk attitudes among customers. To address this gap, this paper proposes a novel two-stage hotel recommendation model driven by online reviews, incorporating customers’ risk attitudes and personalized preferences. Firstly, this paper utilizes the Latent Dirichlet Allocation (LDA) topic extraction model and the sentiment analysis tool to extract public and personalized preferences from hotel reviews and customers’ historical reviews respectively. Secondly, in the first stage of hotel recommendation, this paper constructs a hotel filtering mechanism to cater to customers with different risk attitudes, ensuring that the recommended hotels align with customers’ individual risk tolerance. In the second stage of hotel recommendation, this paper introduces the cosine similarity algorithm of probabilistic linguistic term sets, enabling more accurate and tailored recommendations. Finally, to verify the applicability of the proposed model, a case study is conducted using real data from TripAdvisor.com. The results of the comparative analysis indicate that the proposed model outperforms other recommendation models.
考虑客户风险态度和个性化偏好的在线评论驱动两阶段酒店推荐模型
酒店推荐模型为顾客选择理想酒店提供了重要参考,帮助他们克服信息超载问题。然而,以往的模型主要侧重于捕捉公众偏好,忽视了顾客的个性化偏好或不同的风险态度。针对这一缺陷,本文提出了一种新颖的由在线评论驱动的两阶段酒店推荐模型,并将顾客的风险态度和个性化偏好纳入其中。首先,本文利用 Latent Dirichlet Allocation(LDA)主题提取模型和情感分析工具,分别从酒店评论和顾客历史评论中提取公共偏好和个性化偏好。其次,在酒店推荐的第一阶段,本文针对不同风险态度的客户构建了酒店过滤机制,确保推荐的酒店符合客户的个人风险承受能力。在酒店推荐的第二阶段,本文引入了概率语言术语集的余弦相似度算法,使推荐更加准确,更具针对性。最后,为了验证所提模型的适用性,本文使用 TripAdvisor.com 的真实数据进行了案例研究。对比分析的结果表明,所提出的模型优于其他推荐模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Omega-international Journal of Management Science
Omega-international Journal of Management Science 管理科学-运筹学与管理科学
CiteScore
13.80
自引率
11.60%
发文量
130
审稿时长
56 days
期刊介绍: Omega reports on developments in management, including the latest research results and applications. Original contributions and review articles describe the state of the art in specific fields or functions of management, while there are shorter critical assessments of particular management techniques. Other features of the journal are the "Memoranda" section for short communications and "Feedback", a correspondence column. Omega is both stimulating reading and an important source for practising managers, specialists in management services, operational research workers and management scientists, management consultants, academics, students and research personnel throughout the world. The material published is of high quality and relevance, written in a manner which makes it accessible to all of this wide-ranging readership. Preference will be given to papers with implications to the practice of management. Submissions of purely theoretical papers are discouraged. The review of material for publication in the journal reflects this aim.
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