gTravel: Weather-Aware POI Recommendation Engine for a Group of Tourists

Rajani Trivedi, Bibudhendu Pati, Subhendu Kumar Rath
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Abstract

Weather is a big factor in tourist decisions, andcertain places or events aren’t even recommendedduring dangerously bad weather. It is difficult to providea better recommendation to a group of tourists in thesecircumstances. We propose gTravel, a weather assistantframework that predicts weather in specified pointsof interest for a group of tourists. We demonstratehow prior knowledge of climatic patterns at a POI,as well as prior insights into how visitors rank theirdestinations in a variety of weather conditions, can helpimprove choice reliability. According to our findings, therecommendations are significantly more valid, and therecommended remedy is more comfortable.
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gTravel:为一群游客提供天气感知POI推荐引擎
天气是影响游客决定的一个重要因素,在危险的坏天气里,某些地方或活动甚至不被推荐。在这种情况下,很难向一群游客提供更好的建议。我们提出了gTravel,这是一个天气助手框架,可以为一群游客预测特定兴趣点的天气。我们展示了POI的气候模式的先验知识,以及游客如何在各种天气条件下对目的地进行排名的先验见解,可以帮助提高选择的可靠性。根据我们的研究结果,这些建议明显更有效,并且推荐的补救措施更舒适。
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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