The massive growth of internet users nowadays can be a big opportunity for the businesses to promote their services. This opportunity is not only for e-commerce, but also for other e-services, such as e-tourism. In this paper, we propose an approach of personalized recommender system with pairwise preference elicitation for the e-tourism domain area. We used a combination of Genetic Agorithm with pairwise user preference elicitation approach. The advantages of pairwise preference elicitation method, as opposed to the pointwise method, have been shown in many studies, including to reduce incosistency and confusion of a rating number. We also performed a user evaluation study by inviting 24 participants to examine the proposed system and publish the POIs dataset which contains 201 attractions used in this study.

如今互联网用户的大量增长可能是企业推广其服务的大好机会。这个机会不仅适用于电子商务，也适用于其他电子服务，例如电子旅游。在本文中，我们提出了一种针对电子旅游领域的具有成对偏好启发的个性化推荐系统方法。我们使用了遗传算法与成对用户偏好诱导方法的组合。与逐点方法相比，成对偏好引出方法的优点已在许多研究中得到证明，包括减少评分数字的不一致和混淆。我们还通过邀请 24 名参与者检查提议的系统并发布包含本研究中使用的 201 个景点的 POI 数据集来进行用户评估研究。