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刘文龙,黄维. 基于领域词典的留园构成要素情感分析[J]. 科学技术与工程, 2021, 21(8): 3174-3179.
LIU Wenlong.Clustering sentiment analysis of the constituent elements of garden stay based on domain dictionary[J].Science Technology and Engineering,2021,21(8):3174-3179.
基于领域词典的留园构成要素情感分析
Clustering sentiment analysis of the constituent elements of garden stay based on domain dictionary
投稿时间:2020-05-29  修订日期:2020-11-28
DOI:
中文关键词:  情感分析  留园  要素聚类  领域词典
英文关键词:sentiment analysis  stay garden  clustering of elements  domain dictionary
基金项目:
     
作者单位
刘文龙 清华大学
黄维 清华大学
摘要点击次数: 156
全文下载次数: 34
中文摘要:
      在对旅游景点的评论挖掘中常以多景点横向对比为研究切入点,为景点间的横向比较及游人选择景点服务,而较少针对单一景点深入分析,为景点单要素精准提升服务。本文以留园为例,按照构成元素构建聚类,并基于领域词典的进行整体与分要素聚类的情感分析。结果表明留园中“山石”要素相关的正面情感占比66%,低于分要素平均正面情感78.3%。可见基于园林构成要素聚类分析对可帮助精准提取互联网评论情感分析,该方法对园林等旅游景点管理方优化、品牌形象提升提供了一种易于操作的、更精准的理论与方法。
英文摘要:
      In the mining of comments on tourist attractions, horizontal comparison of multiple attractions is often used as the research entry point, for horizontal comparison between attractions and for tourists to choose attractions, but less in-depth analysis of single attractions, for the single element of attractions to improve the service accurately. This article takes the Lingering Garden as an example, constructs clusters according to constituent elements, and conducts sentiment analysis of clustering of whole and sub-elements based on domain dictionary. The results showed that the positive emotions related to the "mountain stone" elements in the Lingering Garden accounted for 66%, which was lower than the average positive emotions of the sub-elements by 78.3%. It can be seen that cluster analysis based on garden constituents can help accurately extract sentiment analysis of Internet reviews. This method provides an easy-to-operate and more accurate theory and method for optimizing and improving gardens and other tourist attractions.
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