上下文感知旅游推荐系统研究综述

随着人们生活水平的提高,旅游已成为一项普遍的休闲活动,进而推动了旅游推荐方面技术的研究。与传统推荐系统相比,除了考虑游客和旅游产品的相关特征之外,旅游推荐系统的推荐质量在很大程度上受到位置、时间、天气、游客社交群体等上下文信息的影响。本文首先给出上下文感知旅游推荐系统的总体框架;然后对位置、时间、游客社会化网络和多维上下文等4类典型的上下文信息在旅游推荐系统中的应用进行了详细考察,并对综合应用各种上下文信息的旅游推荐系统进行了分析;从旅游推荐产品的角度对推荐系统进行分类考察;最后讨论了上下文感知旅游推荐系统目前面临的重点和难点问题,指出下一步的研究方向。

Review of a context-aware travel recommendation system

With improved living standards, tourism has become a common leisure activity that has promoted the research of tourism recommendation technologies. When compared with a traditional recommendation system, the quality the proposed system is considerably influenced by the contextual information, including the location, time, weather, and social groups of tourists, in addition to relevant characteristics of tourists and tourism products. In this study, we provide the overall framework of a context-aware tourism recommendation system. The application of four typical types of context information in the travel recommendation system, such as the location, time, visitor social network, and multidimensional context, is investigated in detail, and the tourism recommendation system that comprehensively applies various types of contextual information is analyzed. Further, the tourism recommendation system is classified and inspected from the perspective of the tourism recommendation products. Finally, key and difficult problems faced by the context-aware tourism recommendation system are discussed, and the future research direction is identified.