基于用户生成内容的大型商场情感地标提取方法

An Extraction Method of Emotional Landmarks in Large Malls Based on User-Generated Content

用户情感对空间注意力、决策和记忆力具有重要影响。情感与地标关联可在增强用户认知地图能力的同时,提高导航效率。当前研究侧重于情感地标在导航中的作用,对其在复杂室内环境中的提取方法关注较少。以大型商场为研究对象,提出基于用户生成内容的情感地标显著度定量评价模型,进而实现室内情感地标的自动化提取。首先,利用网络爬虫技术获取某大型商场的用户评论数据;其次,基于SnowNLP对用户评论进行情感分析,并将分析结果扩展至认知显著性度量体系中;然后,利用层次分析法和指标相关性的组合赋值法计算显著度指标的权重,构建情感地标显著性综合评价模型;最后,利用层次聚类算法提取分级地标,依据分级地标设计符合用户认知的多尺度室内导航地图,通过用户实验验证地标提取方法的可用性。该研究推动室内导航地图设计的标准化,为室内智能化导航服务提供有益的补充。

Objectives:User emotions have a significant impact on spatial attention,spatial decisionmaking,and spatial memory.Emotions associated with landmarks can improve navigation efficiency while enhancing users'cognitive map abilities.The previous studies focused on the role of emotional landmarks in navigation,but few studies paid attention to landmark extraction methods in complex indoor environments.Methods:This paper proposes a quantitative model of salience to automate the extraction of emotional landmarks in large shopping malls based on user-generated content.First,we obtain user comment data of a large shopping mall using web crawler technology.Second,we conduct the sentiment analysis on user com‐ment and extend the results to landmark cognitive salience.Finally,we combine the analytic hierarchy process and criteria importance through intercriteria correlation to calculate the weights of indoor landmark salience indicators and construct a quantitative evaluation model of emotional landmark salience.Results:We extract hierarchical landmarks using hierarchical clustering algorithms,design multi-scale indoor navigation maps based on hierarchical landmarks to meet user cognition,and verify the usability of the landmark extraction method by user experiments.Conclusions:This paper can promote indoor navigation map design standardization and provide a valuable complement to intelligent indoor navigation services.