计算机与现代化Issue(8)：31-38,56,9.DOI:10.3969/j.issn.1006-2475.2025.08.005
用户评论数据中城市街区细粒度主观感知发现
Discovery of Fine-grained Subjective Perception of Urban Blocks in User Comment Data
摘要
Abstract
As one of the important dimensions for evaluating urban construction and planning,the subjective perception of urban blocks will help to create a more humane and livable urban space.Based on the representation learning technology and combined with the content of user comments,this paper discovers the structural characteristics between the neighborhood and the subjec-tive perception,and solves the problems of coarse granularity and lack of data in the existing neighborhood perception.Firstly,a fine-grained perception category system is proposed,which analyzes the perception dictionary and POI(Points of Interest)user comment data,analyzes the subject words by LDA and combined with hierarchical clustering to construct a fine-grained street perception category.Secondly,in order to solve the problem of incomplete data,a similarity-weighted k-nearest neighbor filling method is designed,which effectively supplementes the missing POI evaluation content through the information of large cat-egory,small category,and geographical location.Finally,the autoencoder is used to transform the neighborhood perception into potential feature vectors.The real dataset of Beijing is used to evaluate the grading and ranking of housing prices in the neighbor-hood,and the effectiveness of the proposed method is verified.关键词
城市感知/细粒度感知/缺失值填充/表示学习/KNNKey words
urban perception/fine-grain perception/missing value padding/representation learning/KNN分类
信息技术与安全科学引用本文复制引用
孙焕良,李宇航,刘俊岭,许景科..用户评论数据中城市街区细粒度主观感知发现[J].计算机与现代化,2025,(8):31-38,56,9.基金项目
国家自然科学基金资助项目(62073227) （62073227）
国家重点研发计划课题(2021YFF0306303) （2021YFF0306303）
辽宁省教育厅项目(LJKMZ20220916,JYTMS20231596) （LJKMZ20220916,JYTMS20231596）
