可持续城市旅行建模：将 CO2e 排放、受欢迎程度和季节性整合到旅游推荐系统中
Modeling Sustainable City Trips: Integrating CO2e Emissions, Popularity, and Seasonality into Tourism Recommender Systems
AI总结：
本文提出融合交通 CO2e 排放、目的地热度与季节性需求的复合可持续性指标，并通过用户研究确定权重，将其整合进城市旅行推荐系统。
摘要：
旅游业不仅影响旅游产业本身，也影响社会以及环境、当地企业和居民等利益相关方。旅游推荐系统（TRS）能够引导旅行者前往负面影响最小的目的地，从而在促进可持续旅游方面发挥关键作用。本文面向城市旅行 TRS，提出一种基于用户出发地和旅行月份的复合可持续性指标。该指标整合不同交通方式的 CO2e 排放，并分析目的地受欢迎程度与季节性需求。我们基于来自 Tripadvisor 和 Google Trends 数据的用户评论、兴趣点和搜索趋势来量化城市受欢迎程度。为计算季节性需求指数，我们利用来自 TourMIS 和 Airbnb 的数据。我们开展了一项用户研究，以探究旅行决策中的基本权衡，并确定所提出指标的权重。最后，我们展示了该指标在 TRS 中的整合，说明其能够提供可持续的城市旅行推荐。本工作通过整合可持续性度量并促进 TRS 的负责任推荐，为未来研究奠定基础。
英文摘要：
Tourism affects not only the tourism industry but also society and stakeholders such as the environment, local businesses, and residents. Tourism Recommender Systems (TRS) can be pivotal in promoting sustainable tourism by guiding travelers toward destinations with minimal negative impact. Our paper introduces a composite sustainability indicator for a city trip TRS based on the users' starting point and month of travel. This indicator integrates CO2e emissions for different transportation modes and analyses destination popularity and seasonal demand. We quantify city popularity based on user reviews, points of interest, and search trends from Tripadvisor and Google Trends data. To calculate a seasonal demand index, we leverage data from TourMIS and Airbnb. We conducted a user study to explore the fundamental trade-offs in travel decision-making and determine the weights for our proposed indicator. Finally, we demonstrate the integration of this indicator into a TRS, illustrating its ability to deliver sustainable city trip recommendations. This work lays the foundation for future research by integrating sustainability measures and contributing to responsible recommendations by TRS.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
