Xnavi
Xnavi
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DOI：
10.1145/3191759
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发表时间：
2018-03
影响因子：
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通讯作者：
Masato Nomiyama;Toshiki Takeuchi;Hiroyuki Onimaru;T. Tanikawa;Takuji Narumi;M. Hirose
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文献类型：
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作者：
Masato Nomiyama;Toshiki Takeuchi;Hiroyuki Onimaru;T. Tanikawa;Takuji Narumi;M. Hirose
尽管由于互联网的普及，越来越多的人现在参与到旅行计划中来，但旅行者自己计划旅行仍然很困难。对于乘坐汽车的游客来说，这尤其困难，因为他们有几个可到达的地方可供选择。为了方便地制定行程，旅行者需要一个旅行计划系统，该系统建议两种类型的体验：具有旅游地区特征的体验和源于前一种体验之间流动的体验。现有的系统没有列出旅行者感兴趣的具体的自发体验。为此，提出了基于经验流的驾驶员出行规划系统Xnavi，它提供了这些类型的体验。为了推荐体验流，Xnavi使用基于TF-IDF方法的自然语言处理提取与旅游区域相关的体验关键词，并基于驾驶历史的关联分析提取旅游景点属性流。对所提出的方法进行了试验和用户研究。结果表明，Xnavi在推荐体验和满足游客计划方面是有效的。
Though an increasing number of people is now involved in travel planning owing to the spread of the internet, it is still difficult for travelers to plan trips on their own. It is especially difficult for tourists using automobiles because they have several choices of accessible places. To make itineraries easily, travelers require a travel planning system that suggests two types of experiences: experiences characterizing the travel area and experiences stemming from a flow between the former experiences. Existing systems do not list specific spontaneous experiences of interest to travelers. In response, Xnavi, a travel planning system for drivers based on experience flows, is proposed, which provides these types of experiences. To recommend experience flows, Xnavi extracts experience keywords related to the travel area using natural language processing based on the TF-IDF method and also extracts flows of tourist attractions' attributes based on association analysis of driving histories. Trials of the proposed method and a user study were conducted. The results show that Xnavi is effective at suggesting experiences and satisfying tourists with their plans.