东北大学学报:自然科学版 ›› 2019, Vol. 40 ›› Issue (11): 1667-1672.DOI: 10.12068/j.issn.1005-3026.2019.11.026

• 管理科学 • 上一篇    

基于酒店特征信息和在线评价信息的酒店选择

陶玲玲, 尤天慧, 袁媛   

  1. (东北大学 工商管理学院, 辽宁 沈阳110169)
  • 收稿日期:2019-01-31 修回日期:2019-01-31 出版日期:2019-11-15 发布日期:2019-11-05
  • 通讯作者: 陶玲玲
  • 作者简介:陶玲玲(1991-),女,辽宁铁岭人,东北大学博士研究生; 尤天慧(1967-),女,黑龙江宾县人,东北大学教授,博士生导师.
  • 基金资助:
    国家自然科学基金资助项目(71771043).

Hotel Selection Based on Information of Hotel Features and Online Ratings

TAO Ling-ling, YOU Tian-hui, YUAN Yuan   

  1. School of Business Administration, Northeastern University, Shenyang 110169, China.
  • Received:2019-01-31 Revised:2019-01-31 Online:2019-11-15 Published:2019-11-05
  • Contact: YOU Tian-hui
  • About author:-
  • Supported by:
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摘要: 为辅助游客通过旅游网站进行酒店选择,提出了一种基于旅游网站提供的备选酒店特征信息和在线评价信息的酒店选择方法.首先,基于酒店特征信息和在线评价信息构建备选酒店有向加权图,依据备选酒店特征信息,基于离差最大化法对酒店特征进行客观赋权,并采用简单加权法确定有向加权图结点权重,依据备选酒店间在线评价信息的比较关系确定有向加权图的有向边及有向边权重;然后,基于PageRank算法原理给出备选酒店排序值求解算法;最后,以基于缤客网站提供的酒店特征信息和在线评价信息进行酒店选择.结果说明了提出方法的有效性和可行性.

关键词: 酒店特征信息, 在线评价信息, 有向加权图, PageRank, 酒店选择

Abstract: In order to assist tourists to select hotels through tourism websites, a method for selecting desirable hotels is proposed based on features information and online ratings information of alternative hotels provided by tourism websites. Firstly, the directed and weighted graph of alternative hotels is constructed, in which hotel features are weighted objectively by the maximum deviation method based on hotel features information and then the node weights of directed weighted graph are determined by the simple weighting method. The directed edge and its weight are determined by comparing the online ratings information of node hotels. Then, the algorithm for calculating the sorting value of alternative hotels is given based on the principle of PageRank algorithm. Finally, in order to verify the effectiveness and feasibility of the proposed method, a case study on desirable hotel selection is proposed based on the information of hotel features and online ratings from the Booking.com website.

Key words: hotel features information, online ratings information, directed and weighted graph, PageRank, hotel selection

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