图书情报工作 ›› 2022, Vol. 66 ›› Issue (7): 132-143.DOI: 10.13266/j.issn.0252-3116.2022.07.013

• 知识组织 • 上一篇    下一篇

景点文化资源标签自动生成与应用研究

郑淞尹, 谈国新   

  1. 华中师范大学国家文化产业研究中心 武汉 430079
  • 收稿日期:2021-10-29 修回日期:2022-01-16 出版日期:2022-04-05 发布日期:2022-04-15
  • 通讯作者: 谈国新,教授,博士生导师,通信作者,E-mail:gxtan@mail.ccnu.edu.cn。
  • 作者简介:郑淞尹,博士研究生。
  • 基金资助:
    本文系文化和旅游行业标准化研究项目"乡村文化资源分类体系研究"(项目编号:WH/Y09-2019)和国家文化和旅游科技创新工程项目"湖北省非物质文化遗产数字化传播创新平台研发"(项目编号:2019-008)研究成果之一。

Research on Automatic Generation and Application of Cultural Resource Tags of Scenic Spots

Zheng Songyin, Tan Guoxin   

  1. National Research Center of Cultural Industries, Central China Normal University, Wuhan 430079
  • Received:2021-10-29 Revised:2022-01-16 Online:2022-04-05 Published:2022-04-15

摘要: [目的/意义] 为旅游景点生成高质量的文化资源标签,解决文化旅游服务中信息检索困难、推荐形式单一的问题。[方法/过程] 首先,设计包含显式和隐式两种标签类型的文化资源标签体系;然后,提出基于特征词筛选和噪声词过滤的显式标签生成方法,以及设计隐式标签中文化感知强度和文化感知相似度的计算方法,并基于以上方法生成景点文化资源标签;最后,针对旅游信息服务中的不同场景,提出基于文化资源标签的检索和推荐方法。[结果/结论] 以武汉市的真实旅游数据为例进行实证研究,结果表明,基于本文方法生成的标签能够准确刻画景点的文化资源特征,基于标签的检索和推荐方法均具备较强的可解释性,可有效提升信息服务的透明度和用户对结果的信任度,对其他领域的推荐解释性研究具有参考价值。

关键词: 旅游信息服务, 标签生成, 资源检索, 旅游推荐

Abstract: [Purpose/Significance] To generate high-quality cultural resource tags for scenic spots, and solve the problems of difficult information retrieval and signal recommendation form in cultural tourism services.[Method/Process] First, a tag system for cultural resources including explicit and implicit tag types was designed; then, an explicit tag generation method based on feature word filtering and noise word filtering was proposed, and the calculation method of cultural perception intensity and cultural perception similarity in implicit tags was designed, and cultural resource tags of scenic spots were generated based on the above methods; finally, for different scenarios in tourism information services, retrieval methods and recommendation methods based on cultural resource tags were provided.[Result/Conclusion] Taking the real tourism data of Wuhan as an example to conduct empirical research. The results show that the tags generated based on this method can accurately describe the cultural resource characteristics of scenic spots, and the retrieval and recommendation algorithms based on tags have strong interpretability, which can effectively improve the transparency of information services and users' trust in the results, and have reference value for recommendation and interpretation research in other fields.

Key words: tourism information service, tag generation, resource retrieval, travel recommendation

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