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基于语义Web的旅游路线个性化定制系统

姬鹏飞 1,李远刚 2,3,卢盛祺 1,2,戴开宇 1,4   

  1. (1.复旦大学 软件学院,上海 200433; 2.上海财经大学 信息管理与工程学院,上海 200433; 3.大连外国语大学 软件学院,辽宁 大连 116044; 4.上海市数据科学重点实验室 上海 200433)
  • 收稿日期:2015-08-26 出版日期:2016-10-15 发布日期:2016-10-15
  • 作者简介:姬鹏飞(1994—),男,学士,主研方向为语义Web;李远刚、卢盛祺,博士研究生;戴开宇,讲师、博士。
  • 基金资助:
    复旦大学本科生学术研究资助计划项目。

Personalized Customization System of Travel Route Based on Semantic Web

JI Pengfei  1,LI Yuangang  2,3,LU Shengqi  1,2,DAI Kaiyu  1,4   

  1. (1.Software School,Fudan University,Shanghai 200433,China;2.School of Information Management and Engineering,Shanghai University of Finance and Economics,Shanghai 200433,China;3.School of Software,Dalian University of Foreign Languages,Dalian,Liaoning 116044,China;4.Shanghai Key Laboratory of Data Science,Shanghai 200433,China)
  • Received:2015-08-26 Online:2016-10-15 Published:2016-10-15

摘要: 自助游逐渐成为当今旅游的主要方式,但由于互联网信息过载以及基于文本匹配的搜索机制等问题,用户需要花费大量时间和精力自行完成旅游路线的规划。为给用户提供个性化、可定制的旅游规划服务,提出基于语义Web技术的旅游路线个性化定制系统。构建旅游景点的领域本体模型,在半监督条件下完成景点实例的填充,结合中文分词、词性标注以及本体用户建模等技术,实现用户检索需求的解析并根据用户兴趣模型对检索结果进行分类排序,利用景点间的语义关联完成时空相关的路线扩展。系统性能测试和可用性评估结果表明,该系统具有较高的查准率和查全率,可实现旅游线路的个性化定制。

关键词: 旅游路线, 个性化定制, 语义Web, 用户建模, 时空关联, 信息检索

Abstract: In recent years,independent travel gradually becomes the mainstream of traveling.However,due to the Internet information flooding and search mechanism based on text matching,much attention and effort have to be paid by users to search and organize a tour route.To provide personalized and customized travel planning services for users,this paper proposes a personalized customization system of travel route based on semantic Web technology.The domain ontology model of tourist attractions is constructed and attraction instances are filled under semi-supervised conditions.User retrieval need interpretation is implemented and the retrieval results are sorted according to user’s interest model by applying Chinese word segmentation and part of speech tagging and ontology-based user modeling techniques.Finally,the system completes the time-space correlation extension by using semantic correlation between attractions.System performance test and usability evaluation results indicate that the system has high precision and recall,and it implements personalized and customized travel routes.

Key words: travel route, personalized customization, semantic Web, user modeling, space-time correlation, information retrieval

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